Robotics and Autonomous Systems ELSEVIER Robotics and Autonomous Systems 15 (1995) 143-169

Living Machines

Brosl Hasslacher a,*, Mark W. Tilden h a Theoretical Division, Los Alarnos National Laboratory, Los Alamos, NM 87545, USA t~ Biophysics Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA

Abstract

Our aim is to sketch the boundaries of a parallel track in the evolution of robotic forms that is radically different from any previously attempted. To do this we will first describe the motivation for doing so and then the strategy for achieving it. Along the way, it will become clear that the machines we design and build are not robots in any traditional sense. They are not machines designed to perform a set of goal-oriented tasks, or work, but rather to express modes of survivalist behavior: the survival of a mobile autonomous machine in an a priori unknown and possibly hostile environment. We use no notion of conventional "intelligence" in our designs, although we suspect some strange form of that may come later. Our topic is survival-oriented machines, and it turns out that intelligence in any sophisticated form is unnecessary for this concept. For such machines, if life is provisionally defined as that which moves for its own purposes, then we are dealing with living machines and how to evolve them. We call these machines biomorphs (BiOlogical MORPHology), a form of parallel life.

Keywords: Adaptive minimal machines; Robobiology; Nanotechnology

1. Introduction to hiomorphic machines scale of the cell, using the cells' ingredients, power sources and ATP engines. Doing that would not One difference between biological carbon recover ceil-centered biology, but manufacture based life forms and the mobile survival machines novel, potentially useful life forms that have ap- we will discuss are materials platforms, which can parently escaped the normal path of evolution. be metals, plastics, silicon - a large variety of What is different about biomorphic machines materials, but as we take these principles and from typical mobile platform designs is not their descend in scale, it becomes clear that we could materials base but how they are organized. They use many of the ready made protein structures use a dynamical, non-symbolic internal world rep- provided by molecular cell biology for other pur- resentation and compliant, bi-directional, interac- poses. We could in principle self-assemble this tive response where the external world assumes a new machine life out of carbon chemistry at the crucial role. In this they have much in common with biological forms which is not accidental; these machines are designed along biological * Corresponding author. E-mail: [email protected] or paradigms rather than on first principle notions [email protected] of how such machines should be organized. We

Elsevier Science B.V. SSDI 0921-8890(95)00019-4 144 B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 take the viewpoint that such principles will have 2. Biomorphic architectures and global machines to be discovered by experiment rather than postu- lated by pure reason. In a sense these machines Biomorphic architecture is autonomous ma- are evolved by physicists and engineers looking chine architecture modeled on compliant skeletal through biological eyes. Ultimately however, wandering mechanisms found in biology. All ef- biomorphs are self-designed by the machines' own fective computation is done in analog and from emergent survival capabilities. the periphery inward. It is modular and tiered. This is a study in experimental machine mor- No digital computation is ever done within the phology and psychology. Over 70 working ma- motion platform, although digital pulse trains are chines have been built and principles extracted to used for motor drive and control. The essence is design more efficient but less complex machines a core of electronic neurons that is bidirectionally with better cost-versus-survival functionality. We connected to standard sensors and "smart" me- consider this field an experimental science in chanical appendages that locally do much of the which we both learn from the machines and are immediate computation necessary for their func- for the moment their evolutionary agents. tion. The simplest way to describe a biomorphic From a systems viewpoint the entire mecha- device is to say that the whole machine acts as an nism is a single analog computer with a local analog computer, designed along biological modular architecture, where analog computation paradigms, to move in, interact with, and survive occurs in two realizations: mechanical at the ma- in an unknown but fractal external world. There chine periphery and electronic at the core. The is no notion of programming, but rather adaptive, simplest non-trivial morphic architecture is a mo- parallel reconfiguring of signals in neuron cir- bile survival platform using only mechanics and cuits, typically in ring topologies. These structures an electronic core. This allows for sufficient, if compute, but not in any digital sense. This leads not efficient, negotiation of undefined, complex to the idea of a biomorphic architecture. terrains.

Plate 1. "Bug of the Badlands". B. Hasslacher, M. W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 145

Operationally, a biomorphic machine is a A soft machine is a biologically based concept global rather than local object despite its modular in which the machine forms its behavior through construction. The entire device acts as a unit with interactions with a complex and a priori unknown mesoscale properties that could not be inferred environment. This changes with time and interac- from a description of its components. In this way tion; it is dynamic, and has few, if any, state it resembles cellular automata which are collec- consistencies between modes. It is put in opposi- tions of simple finil:e state machines whose time tion to a hard machine whose behavior is sharply evolution proceeds by simple rules. Nevertheless defined from the start by look-up tables, branch- the range of behaviors possible from such a setup ing logic or other conventional programming extends from trivial fixed point behavior to Tur- schemes. ing machines. These behaviors are collective or emergent and arise at the mesoscale of the sys- 2.2. Walkers tem. An example is the cellular automata model One imagines the following picture: there ex- for the Navier-Stokes equation for fluids; the ists some roughly fractal world that we wish a collective behavior at the mesoscale of a very machine to negotiate and survive. The machine simple set of cellular automata rules. In biomor- should extract power from its environment - phic architectures we do not have finite state power can be thought of as a form of food and it machines in the normal sense, since there is no should always look for better and more reliable concept of digital or symbol, nor preset update sources of power, but this ideal case, however rules, only dynamic interactions among the parts desirable and practical, is not necessary to the of the machine. However, the analogy is familiar idea. In practice the fractal world is some me- territory and a good one to keep in mind. chanical terrain and the machine must move and Although trivial pieces of biomorphic ma- react to it. The terrain is always assumed dynamic chines, such as an entire leg can be removed, and even hostile - populated with other life altered or damaged without altering the ma- forms moving for their own reasons and searching chines' behavior, modifications to the internal for food. We choose a walking mode rather than neural architecture', will alter global response flying, swimming or wheels as a first step for drastically. Most biomorph machine "nets" em- several reasons. First a walker can efficiently ployed so far are in loop and/or link ring struc- negotiate severe terrains without constriction, a tures with a single minimal control core that once lesson learned from biology. Second, walkers pro- set cannot be topologically altered without creat- vide very important visual clues to their builders ing a completely new class of behaviors. There is as to whether they are operating properly and aid no concept of smooth deformation away from the immeasurably in indicating solutions to the con- innermost minimal core. The way to increase the vergence of the "creatures" neural core. Because functionality of the machine is to add additional most higher biological life forms are walkers, functional ring structures that can be smoothly people have evolved an acute sense of "body deformed. The upper bound for such designs is language" allowing us to immediately recognize obviously infinite, but there is an efficient lower whether a walker is operating properly and in bound architecture that implies the idea of a what mode. With wheeled devices this is almost minimal survival neuron network that we will impossible. Again we are taking many cues and describe, following some background theory on strategies from biological behavior. general living machine architectures. 2.1. Soft machines 2.3. Layered autonomy First we describe a setup designed to produce Next we use an important clue from biological sharp mental images with a minimum of formal- architectures, the idea of layered autonomy, ism and introduce a lexicon that we have found around which the entire architecture is con- convenient to describe these machines. structed. 146 B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

2.4. Mechanical layer 2.5. Neuron core

Biomorphic walker legs must be able to solve In analogy to biological organisms, we use an the problems of balance dynamically as indepen- artificial nervous system with adaptive control to dent units, separate from knowledge of or help produce appropriate adaptive walking gaits for from the rest of the organism. This can be done these machines. We equip the legs with explicit in several ways. We chose the simplest in concep- and implicit local sensors that allow it to make a tion but not in execution, namely "smart" me- highly abstract image of its immediate environ- chanical legs with low degrees of freedom (DOF) ment. Distal sensors are irrelevant for sufficient but high degrees of structural compliance. They minimalist machines; they do not need the cogni- compute balance in mechanical analog, using bio- tive skills to process such information. Explicit logically motivated mechanical structures with sensors can be of many kinds, for the purposes of fuzzy logic joints and unavoidable stochastic slop. a simple picture one can imagine them to be There is no digital processing whatsoever done simple impact or proximity sensors. Implicit sens- on the machine. It is both unnecessary and, in ing in the biomorphic case is in the form of implementation, very costly in terms of general- torque feedback from all leg motors, giving a ized computational resources. Each leg balances direct and sufficient indication of terrain com- itself in parallel with the others. Compliant me- plexity. These signals are carried by the electronic chanical legs are also appropriate objects for in- analog of a nervous bundle to the central neuron teracting with a hard fractal world. They can be core which shapes and delays a cycle of timing made of such size and materials to negotiate signals to the drive motors in a dynamic fashion. complex and rough terrain with minimal damage If the nervous core has been calibrated appropri- to either walker or environment. As well, they ately for the mechanical elements of its physical can double as manipulators so that the body, the emergent behaviors are recognizable function/complexity ratio of the machine is opti- walking gaits for the machine. mized. All of this processing is analog, constructing a

Conventional Biomorphic Robotic Designs Design Structure

World

World

World

Hard Demarkation Boundaries with one-way Computational Structure Flexable (soft) Demarkation Boundaries with Bidirectional Computation Structure Fig. 1. Comparison of conventional vs. biomorphic architectures. B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 147 primitive, dynamic, but sufficient internal neuron condensed representation of the external world. core representation of the machine's state in the Outwards the mechanical body, also computing external world. As it is the only representation continuously, can interact with the external world, biomorphs have of the external world, this sharply but has no knowledge that it even belongs to an distinguishes it from strategies using highly de- integrated creature: a sum of components, all tailed, preordained internal world representa- with soft demarcation boundaries, blending to tions and opposite strategies that use no such form survival adequacy. Fig. 2 gives a typical representation. Both these conventional strate- design representation for a quadruped creature, gies have proven, by experiment, to be extremely which can be quickly extended to 6, 8, or 2n costly in computational resources. In contrast, we legged devices (odd number legged devices are have capable walking machines that negotiate possible but ineffective as the odd leg induces a complex unknown terrain using a total of twelve drag on the structure that the control core can transistors as the computational core. make little use of). The output of the neuron core propagates down the neural bundle to drive motors and sensors, modifying their behavior and closing the 3. Internal landscapes and roaming space loop. As the machine interacts with the external world, the internal representation of that world Biomorphic survival traits and behaviors can changes continuously. The neuron core acts as a be emphasized, not set, by the careful matching variable-rate, short-term memory whose indepen- of the variables among layered components. To dent components have no knowledge of belong- represent this, we chose to equip biomorphic ing to a larger organism. machines with an expandable internal landscape The overall design picture that emerges is a that self-assembles an internal abstract world. single global analog computer whose various This internal representation resides primarily in pieces change realization. They smoothly morph the nervous-network core (Nv) and has severe through several stages: sensors that deliver modi- constraints. Elementary walking gaits are func- fication information to a heuristic neural net tional blocks that become atomic structures. "brain," which influences an independent neuron Through interaction with sensors and motor loads, machine core that ,contains a highly abstract and they loosely couple the whole machine into a

Fig. 2. Biomorph computationalstructure. 148 B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

single system with a global world representation, immediately recognize. By this we mean the ma- giving the machine complex dynamical systems chine develops the ability to find adaptive solu- properties. One learns from dynamical systems tions to complex adaptive problems that are ana- theory never to couple the parts of a nonlinear log, purely parallel, and not symbol based. Intu- machine too tightly if you want complex behavior. itively, such designs would seem to be contradic- Tight coupling, as in programmed tasks, con- tory in their abilities. Experimental evidence strains the development of emergent nonlinear shows, however, that these devices are not just behavior to the point of extinction. These ma- passively convergent on survival solutions, but chines display emergent behavior; from a systems aggressively so. viewpoint the entire machine is a loosely coupled, The ring structures of biomorph nervous net parallel computer. This allows biomorph designs design hinges on the emergent computational not just adaptation to complex terrain, but also properties of biological motor neurons as com- resilience against element damage. Indeed, we pared to the signal adaptation abilities of classic have seen that such designs can withstand up to neural structures. Our artificial motor neurons 80% damage of their systems yet still attempt to work in topological chains, loops, and intersec- continue moving. At this point they are far from tions and act as effective pre-processing elements efficient, but such designs may be sufficient for between the motors and whatever controlling many tasks. So long as a mechanism can remain "head" may direct the mechanism through its moving, it is capable of continuing performance. environment. The design structure of these net- The neural core plays a special role in this works is not unlimited but is constrained by the picture, for it is here that the distillate of all dimensional limits of the machine's morphology, computation done by the periphery of the ma- center of balance, power availability, and motor chine is focused in an abstract and condensed efficiency. The phase space is vast but if design- form. Here presentation is non-symbolic, consist- ers concentrate on minimalist arrangements, ele- ing in the delay and shaping of a chase-series of gant, competent designs emerge. timing pulses that drive the motors of the device. The world is a set of pulse shapes traversing a 3.2. Intelligence ring topology and constantly attempting phase lock synchronization among variable pulse trains. A biomorphic architecture roams in the world There is an internal/external balance set up that and interacts with it, concurrently constructing a is flexible enough to give both reactive and emer- dynamic complex internal representation of the gent behaviors to the machine. external world in its neuron landscape. We could enlarge their internal landscape in an initially 3.1. World representation unconstrained way, for example by providing neu- rons on an analog VLSI chip with free nodes that There are two types of approaches to the the machine could adaptively explore and con- world representation problem in current use. One nect. We conjecture that a form of sub-cognitive uses no internal representation and the other intelligence emerges by interacting and surviving uses a highly detailed representation, which in a hostile and unknown environment, provided though clever, immediately dooms the machine to the machine can encode its experience, not by paralysis or destruction in any environment too symbols, but by altering dynamically the connec- far from its fixed response list. A future aim for tion matrix of a parallel internal landscape. How biomorphic designs is to see if a simple self-as- large this landscape must be is still an experimen- sembled and dynamic internal world representa- tal question, but early indications are that it can tion is a viable alternative. The verdict on this is be surprisingly small. so far open, but biomorphic representations do A nervous net (Nv) acts as a medium that appear capable of a sophisticated and strange supports independent processes passed from neu- type of emergent intelligence that we may not ron to neuron based upon independent neuron B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 149

also the speed at which those legs are used. Single neuron oscillator 10 Nv: Consequently, biomorphic robots have an inher- 16 distinct ent gait stabilization ability regardless of the size process 2 neuron rot patterns (2 distinct 13attems, of their internal controller; if more legs are called O0 & 10) into play, they "run" faster as a natural conse- 4 neuron met 12 Nv: quence of Nv process physics. (3 distinctl~attems ) 32 distinct 0000 process 1000 patterns 1010 3.3. Complexity

000000 14 Nv: One can give a rough argument that the high 1000O0 64 distinct 101000 process degree of complexity that results for such designs ~ 100100 patterns 101010 is possible and perhaps unavoidable. Suppose we had an analog VLSI chip populated with neuron 00000000 10000000 16 Nv: nodes and arranged so that the machine had 10100000 128 distinct dynamic access to node connectivity. This means 10010000 process 10001000 pattems that at every time step the chip was so arranged 10101000 10100100 that the machine could create and destroy links 10101010 among various nodes in a connectivity matrix. Fig. 3. Some distinct process patterns of artificial motor This is different from conventional neural net- neuron (Nv). work configurations as all structure elements are time independent of each other. timing values. The: range of this process space This type of representation is independent of and their interaction dynamics are shown for spatial embedding. It also means that a mecha- some of the smaller, simple ring structures in Fig. nism exists on the chip so that there are two types 3. of distinct operations, creation operators that Individual processes (ls) are independent of connect two nodes and annihilation operators each other in time: so long as they remain more that can cut or destroy the links between nodes. than two neurons away from other processes. The nodes themselves are not static. They con- When processes get close, they mode lock them- tain a signal that varies in time, approximating selves into a common, synchronized time base conventional forms of cellular automaton rule determined by the propagation time t of the updating. Similarly the creation and breaking of trailing process al: that neuron. The result is, node links can be thought of as separate cellular using a 6 neuron core as an example, that in the automata updating according to a different set of two-process pattern 101000, both will cycle in rules. synchronization forever, provided one neuron in The setup in skeletal form consists of two the chain has a shorter t than all the others. independent sets of cellular automata, the node When all neurons ]have approximately the same t, set and the link-unlink set that update according the two processes eventually mode lock into the to rules governed by environment-machine inter- 100100 pattern, where they loop in a fragile 180 actions. Now we loosely couple these two sets of degree mode lock. In a three-process loop, automata according to a third set of coupling 101010, the entire., process chain rotates at the rules also set by the machine. Such a setup is speed defined by the shortest Nv node delay known to produce behavior ranging from collapse (called the "roller-coaster point"). What this of the grid to a fixed point, to exponential explo- means is that the more processes that are intro- sion of connectivity. It also has intermediate duced into an unbalanced Nv loop, the faster it regimes that are capable of emulating the dynam- will travel. This implies that walking robots using ics of strong hyperbolic dynamical chaotic sys- this pattern will be able to increase not only the tems. A fourth regime exists in which strong local number of legs they can use for each gait, but fluctuations of link connectivity occur but the 150 B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

VBUG 1.2 "LOBSTER" Single battery, 0.9 Kg. Metal construction, exoskeletal framework. 6 tactile sensors; 2 antennae, 4 leg. Control core: 12 transistor adaptive Nervous Net (Nv) 16 transistor heuristic Neural net (Nu) 40 transistor motor drive array. Total: 68 transistors Emergent behaviors: -learns walking in 3 sec. from cold start. -obstical avoidance, retreat, attack. -Nu net accelerates Nv net leaming ability by over twice, with 64 possible "moods'. -6 distinct walking gaits (stop, pace, trot, cantor, pronk, crabwalk)

Plate 2.

+ FRONT

motor

======reversable motor

+~

_~v v +

Fig. 4. Vbug 1.2 "Lobster" complete neural structure. B. Hasslacher, M. W.. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 151 overall Hausdorff dimension of the system tends namic problem solving abilities. This was done in rapidly to stable values. a biomorphic device called "Lobster" (see Plate The result is a structure extremely rich in its 2). ability to store and connect information. The complete nervous structure is shown in Fig. 4. As seen, the device is almost a perfectly concentric biomorphic map. The neural layers 4. Super layers - Neural nets mapped a total of 64 possible response influences (based upon external stimulus) onto the 6 distinct There are many traditional alternatives avail- patterns the nervous ring was capable of sustain- able that allow biomorphic machines to do useful ing. The device was quite capable in low stimulus work. If we take a biological paradigm and slave environments but became "confused" when its each nervous neuron from a conventional neural environment became complex (i.e., dynamic, (cognitive) neuron, we now have a structure that rather than stable external stimulus). In such is baseline adaptiw~, but with a heuristic, semi- cases it tended to increase gait cycles as an at- cognitive shell. Sensor structures placed outside tempt to escape the stimulus, and if not possible, this structure are processed by the neural layer to eventually locked itself in a catatonic condition give secondary stimuli to the nervous nets dy- where it remained until the environment settled.

leg mot,

tactile ~+sensor

Fig. 5. Vbug 1.5 "Walkman" complete neural "microcore" structure. 152 B. Hasslacher, M. W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

Baseline emergence revealed itself as the Nv cores damaged the results are fatal. The remaining ability to dynamically re-balance the machine in network would not be rich enough to sustain a complex environments up to one-half the crea- sufficient process spectrum that could generate a ture's height. walking gait. The microcore is composed of three Lobster taught us that combining neural (Nu) morphic elements: Sensors, Neural-net neurons and nervous (Nv) neurons not only yielded much (Nu) and the motor neurons (Nv). The Nu neu- more elaborate behaviors than just neural struc- rons first filter the activation signals in the Nv net tures alone, but that designs could be much denser to regulate gait processes, and secondly effect a if we assumed that the network electronics was change in the topological Nv structure to allow well shielded against damage (damage that would the robot a back-up ability. Without this regula- otherwise force nets into lesser process pattern tion, the Nv 4-node core is sufficient to handle space). Since the Lobster neural structure slaved real-world processing, but not capable of regulat- 2 neurons in 3 ways, and the remaining 4 only ing its responses on power-on. "RC" refers to one way, it was possible to "row-reduce" the "Reticular Cortex" as an analogy to the biologi- network further to a point where all neurons cal mechanism found in living nervous systems were driving at least two motor actions. Initially, that regulate excessive involuntary actions. this pattern seemed too interdependent to assure Because of the flexibility of the symbol lexicon convergence, especially since reducing the ner- used, the microcore diagram is not just a connec- vous core to only 4 neurons would limit possible tion map but also an accurate position map of the gaits to just 3 (stop, walk, dig) from the 6 cur- robots' limbs and sensors. Looking at the robot rently possible. Surprisingly, rather than a low from the top, sensors, motors and control core ability failure, "Walkman" as it is called, turned are all in their appropriate topological position. out to be the most capable of the 6 experimental This is possible for such minimal designs but may walkers built to date. The complete neural struc- fail when designs reach a greater complexity. ture for Walkman is detailed in Fig. 5. Presently we find it very useful. Fig. 5 shows the smallest possible nervous net- There were 3 major results from Walkman work (defined as a "Microcore") for a capable (Plate 3). quadruped with 1.25 DOF per leg. Unlike any First, although the numbers of walking gaits larger ring designs, if sections of this net are were reduced, the network's ability to converge

VBUG 1.5 "WALKMAN" Single battery. 0.7Kg. metal/plastic construction. Unibody frame. 5 tactile, 2 visual sensors. Control Core: 8 transistor Nv. 4 tran. Nu, 22 tran. motor. Total: 32 transistors. Behaviors:

- High speed walking convergence.

- powerful enviro, adaptive abilities

- strong, accurate phototaxis.

- 3 gaits; stop, walk, dig.

- backup/explore ability.

Plate 3. B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 153 on a sufficient walking solution is very fast. The Walkman to climb obstacles twice its own height, standard test is to twist all the legs on a biomorph and lower itself down from obstacles 4 times its machine 180 degrees out of walking phase and height. Interestingly, this gait also made Walk- see how many steps the robot takes to achieve man very difficult to high-center. By placing the forward motion on a level surface. Biomorph device on a hockey-puck sized platform that sus- legs, by convention, are completely unconstrained pended all feet from contact, it did manage to to take advantage of the largest possible effective eventually gain a foothold and escape, by whip- area. Turtle, a basic, non-sensored Nv net on legs ping its limbs around and using angular momen- physically similar to I~bster (6 neuron core), tum to move its torso upon the platform. It was sorts its legs out for forward locomotion in 14 an interesting thing to watch, and something a steps. Lobster, because of its heuristic assist, wheeled device can not manage, as anyone who's manages in only 7 steps. Walkman takes only 1.5 had their car trapped on top of a snow drift can steps and has been seen to frighten researchers attest. and various domestic animals as a consequence. Third, the terrain handling abilities of Walk- Second, althoug]~ there are only 4 time domain man are unexpectedly vast. The device was variables needed to converge a solution for this equipped with pointed rubber feet to give it high network, it took well over a day to find these traction on smooth surfaces and observed many values by experiment, as the degree of influence times as it tried to figure its way across a clut- each neuron had on the others was enormously tered, equipment filled desk. Even against the increased. Many sufficient solutions were found, formidable task of having to crawl over stacked but these often favored either drive or lift (the coat hangers, Walkman eventually found a solu- two essential walking operations) but not both. tion. However, there was one drawback in the Considering the sum of biases on each neuron counterintuitive aspect of Walkmans' success; (Walkman was, like all other biomorph designs, survival ability had gone up exponentially with a far from physically symmetric) the final solution linear decrease in device complexity. This was caused an exaggerated stepping gait that allows annoying as it implied that a much more complex

VBUG 1.1 "SPYDER" Single battery, 1.4Kg., Metal constr. exoskeletal framework, 2.5 DOF per leg. Control Core (Experimental): 4 linked "microcore" Nv structures with adaptive linkages, 4 trans Nu "head". Total: 36 transistors. Emergent Behaviors: -4 quasHndependant control structures converge on a cooperative quadralaterally symetric walking gait after only 10 steps. Leg independence allows for directed action/response despite distributed control.

Plate 4. 154 B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

creature, the "Spyder" walker then under devel- hibit emergent, directed motion. Because Spyder opment, would not have anywhere near the sur- was not originally designed for vivisection, this vival metric of this far simpler creature. theory has yet to be proved in actuality, but a new The Microcore points to a whole new way of generation of cooperative microcore slices is be- looking at creature designs. If we assume the ing designed. microcore as a single, computing element, could The design space for these minimalist devices clusters of these cores produce much larger inter- has, with this observation, expanded exponen- nal computational spaces? Could overall survival tially. We can imagine that groups of biomorphic behaviors emerge from a microcore cluster? As robots could aggregate in social loops, chains, or the smaller robots were of fixed designs, this was even three-dimensional hives with a good chance attempted on the much larger, mechanically com- of recursive symbiontism. That is, we can now plex Spyder, shown in Plate 4. build a "hive" group of minimalist microcore An original attempt at hand-converging a robots and assume this hive will definitely have a tiered Nv core for Spyder took over two weeks to larger collective survival space than the individual arrive at a sufficient walking gait, because of the spaces of its cellular parts. This will not be con- splayed mechanical dependence of 8 motors on a finned until such a hive is made operational and high-compliance, 4-bar linkage frame. Surpris- observed. This is a topic of ongoing research. ingly, using the microcore-cluster controller, Spy- The walkers so far described are the highest der exhibited a sufficient walking gait on first biomorphic forms we have so far built, but by no power on, and an efficient gait only a few adjust- means the only ones. As in biology it is thought ments later. The implications are that microcore that rather than make many phenotypic modifica- clusters can act as adept local processors that are tions to a particular generation of device, it is capable at this higher design plateau. It also easier to make a device, prove a principle, and implies, as each cluster represented one leg in when that principle has been phenotypically mod- this design, that social biomorphism was a distinct ified to exhaustion, build another generation. To possibility even at primitive levels of complexity. describe all the resulting designs would be pro- Micro-cluster Spyder could be theoretically carved hibitably long, so Morph diagrams were invented up into permutations of quadrilateral slices and to give a symbolic representation to the variety of each permutation could still be expected to ex- designs discussed. Morph diagrams conveniently

Morph Symbol Diagrams

Ideal Representation

Eg #1: Biomorph with no Neural Layer

Eg #2: Blomorph with left sensors on nervous layer and right on mechanics World (wall follower design) Fig. 6. "Morph" symbol diagram examples. ' B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 155

intellect that can be quickly understood and con- VBUG1.0 ~ VBUG1.4 trolled by classic domestication techniques. Even "Spyder` (underdevelopment) still, what rules should we formulate as guidelines ~ for designing such survivalist machines? The working assumptions we use for our ma- chines are twofold: VBUG1.1 VBUG1.5 - For an autonomous machine to have a suffi- "Microcom ~ Spyder" "Welkman" cient survival lifetime one must use resilient materials at small enough scales to have a high / weight to power ratio and high structural

VBUGI i 6 strength relative to their environment. O VBUG1.2 'Lobster' V "WalkmanSolar' The second concerns reproduction and power. - Machines cannot be made to reproduce them- VBUG1.3 selves easily, nor would we want them to. At "Turtle" VBUG1.7 (underdevelopment) small scales, with carbon-based materials plat- forms, self-reproduction could be quite dan- gerous. Therefore if machines are to survive Fig. 7. Morph diagrams of prominent biomorphic genotypes. acceptably then we must extend their lifetime to many years in full operation. This means an autonomous machine must extract power from its environment and since that power may be show the structure of biomorphic layers as well as either weak or scarce, it must be able to oper- the Nv mapping w]hich occurs on a particular ate by storage of and access to power on de- physical framework. The convention used is de- mand. In normal scale environments this im- tailed in Fig. 6. plies solar powered machines. As current solar As seen, the morph diagram allows the toroidal cell technology is both inefficient and fragile to biomorphic structure to be mapped onto a plane, mount on any mobile design, one must process allowing for quick ,and efficient sketching of a it through electronic regulation and storage. wide variety of creal:ures and their relative abili- From these observations we can extract some ties. Morph diagrams of the walkers so far built experimental rules of behavior for autonomous and discussed are de.tailed in Fig. 7. machines. Unlike logical axioms we consider these malleable rules subject to alteration if experimen- tal evidence implies they are inadequate. First we 5. Experimental machine morphology note that autonomous control has four principal components: sensation, cognition, locomotion and From an experimental viewpoint, natural pro- manipulation. For our "primordial" machines, cesses have produced such an incredible and ca- only sensation and locomotion are critical to au- pable phase space for life primarily for two rea- tonomous machine operation, although it is possi- sons: living systems are designed and operate to ble for a species to survive on locomotion alone if survive, not to perform blind tasks, and nature is it uses hive or herd dependence. We have found not concerned with the idea of comprehension. the following rules are adequate to ensure the An attempt to build machines using these guide- survival of autonomous machines. lines would appear to be counterproductive, but we submit the opposite is true. By constructing 5.1. Biomorphic laws mechanisms capable of immediate and sustained survival we automatically induce in them an ap- Disregarding other more "esteemed" laws of propriate spectrum of behavior to deal with real robotics, the following are rules that will guaran- world situations. They have a basic core survival tee an autonomous machine's survival. 156 B. Hasslacher, M. IV.. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

Biomorphic survival laws: the space that represents a particular creature's survival metric for a given environment. 1: A machine must protect its existence. Each capability exponent is a milestone of 2: A machine must acquire more energy than it success in a general fractal environment. Conse- exerts. quently many measures will be only part way 3: A machine must exhibit (directed) motion. between states reflecting their degree of survival adequacy. These milestones, taken from experi- Notice that the survivalist laws are very differ- ences in biomorphic studies, are set as: ent from the ethical, and fictitious Asimovian robotic laws. Asimov's laws (in essence, "Protect M- Motion occurs only under application of an humans, obey humans, then look after yourself") external force. do make for good fiction, but inadequate survival M0 No motion abilities. machines. One or more of the above rules, how- M1 Moves deliberately in one dimension. ever, are very easy to incorporate into machine M2 Moves deliberately in 2 dimensions. structure and control systems at a minimalist M3 Moves deliberately in 3 dimensions. level. Complexity is reduced, and survivability is M4 Capable of dual-mode motion with tools, thus enhanced. vehicles, or application specific design elements. 5.2. Architectural maps: "StarNet" representations A- Operates from a non-replenishable energy Watching a million dollar autonomous robot source (battery, power line). bash itself to pieces against a desk edge is a A0 Zero energy consumption or delivery. frustrating experience for designers. No matter A1 Can directly extract/apply external energy how much work went into the robot, it failed a when available. basic preservation instinct obvious to any layman. A2 Can efficiently extract/store/utilize exter- By developing survivor automatons such situa- nal energy. tions can be averted if not completely avoided, A3 Uses focused tactics to efficiently extract, but to do this a survival signature with high store, and utilize external energy. resolution must be worked out for biomorphic A4 Uses planned tactics to efficiently extract/ space. This chapter addresses such a signature. store/utilize external energy. For the purposes of autonomous biomorphic designs, life is defined as that which moves for its P- Negative defensive abilities (physically own purposes. This leads directly to the Biomor- more fragile than environment). phic Laws previously mentioned, which in turn P0 Zero defensive abilities (structural strength form a minimal basis space for a spanning tree of equivalent to environment). survival capability. Biomorphic Laws can then be P1 Flight and/or hide behavior against hostile encoded in 3 general vectors, Mobility, Acquisi- stimulus. tion, and Protection (MAP) where each vector P2 Fight or flight behavior against hostile sti- length is proportional to a biomorphs capability mulus. in that area, and drawn on a planar graph as P3 Tactical fight/flight behavior against hos- indicated in Fig. 8. tile stimulus. This diagram places the three Law vectors P4 Tool, vehicle, or material use in fight/ along the edges of a conical continuous space, flight tactics. increasing from negative survival aspects though layers of exponentially increasing complexity to a high order sentience region. By defining a partic- Obviously beyond a certain machine capability, ular organism's survival proficiency with respect survival metrics loose mutual exclusivity. In the to the Laws, a triangular area can be defined on animal kingdom, the MAP5 metric (i.e., all sur- B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 157

ies that can look after themselves so adeptly that any adequate AI construct acting as its brain could concern itself strictly with the problems of world view problem solving, and not, say, how to get its foot out of a gopher hole. A MAP diagram represents a flexible environ- ment against which biomorphs can be gauged. "Environments" are defined as the dimensional space organisms must exist in, and the conse- quent metric space for a particular biomorph design will depend on the application (for exam- u~ ple, a mechanical fish would not fare too well on Su a MAP space for mountain ranges). To be capa- Sp ble at all biomorphs have to be independent, and that requires an ability to exist in general earth Fig. 8. The complete MAP survival space. environments that are, for all intents, fractal. We assume as the general biomorph environment space the complex surface features found natu- vival exponents equal 5) is set as the domain of rally on the Earth's land masses, at scales ranging implicit survival instincts that are observed in all from 5 cm to 30 cm. This covers biomorph mech- lower animals. Such a metric seems to require anisms that are sufficiently large enough to keep advanced, RNA programmed nervous systems from blowing away due to atmospheric turbu- that, although not sentient by human standards, lence, but small enough for researchers to avoid gives animals the behavioral tactics to sustain excessive design costs. Environment variables themselves. The flocking of birds, homing ability must be adequately, if not completely, described of whales, turtles, etc., are advanced examples of for whatever MAP a mechanism must be mea- instinctive, but unconscious, survival strategies. sured against. For example, at the micron scale The fact that birds don't avoid airports, and nanobots will have to work at, Brownian-motion whales fatally beach themselves in their efforts to forces, gravitational fields, strong material densi- follow their guidance: instinct indicates that these ties, even strong and weak molecular forces must are indeed unconscious, cognitive artifacts. be included as crucial environmental variables. MAP6 is arbitrarily defined as the metric where Consequently successful "nano-morphs" will not all survival aspects blend within high level, sym- be able to use legs or even wheels for motivation, bol-based cognitive abilities, and includes the and their power sources and protective abilities abilities of all large brained animals that can use must employ radically different design physics. syllogistic, problem solving logic. Indeed, this So far, biomorph mechanisms have not gone realm is where most work has been done in trying beyond a MAP3 metric, so for the purposes of to find a functional artificial intelligence (AI). clarity a truncated MAP space is detailed in Fig. Due to the obvious complexity of this region, we 9. will ignore it until there are advanced enough The truncated MAP core shows better detail biomorph mechanisms (and theory) to support of the thermodynamic threshold. This threshold high-level AI constructs. We feel that a study of marks the boundary at which a device neither the high-cognitive regions would not be possible moves, feeds, or protects itself, and is the equiva- until we have a sufficient engineering knowledge lent of death or complete non-function (a uni- of the lower survival dimensions and how to build form MAP0 metric would, for example, represent devices to match them. An indirect aim of this the survival space of a rock). The metric below whole technology is to acquire the knowledge of this defines negative survival aspects and defines how to build capable mechanistic "bodies". Bod- devices that must be moved, fed, and protected 158 B. Hasslacher, M. 14(. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

from outside sources. A good biological example of a uniform MAP- (MAP-negative) metric would be a bird's egg, and a good technical example of would be a personal computer. As suspected, the MAP represents a survival space upon which can be measured not just biomorphs but most simple biological organisms, machines, and even children's toys. As such the MAP is useful to see how biomorphic mecha- aowered nisms rate against these other biomimetic de- ~,- P1.5) n Plantlife vices. A MAP diagram showing some common ~2 P1.5) survival vectors is detailed in Fig. 10. i The vertex of each triangle converges at the ~. PI) Ant point where a particular creature's survival scale 2 P2) is measured. As the three main MAP vectors abound in fuzzy logic connections, for many crea- tures there are half and quarter way points along Fig. 10. MAP vectors for some common "Life" forms. each. For example, most plants are harder than the immediate objects in their vicinity, but do not use flight-or-hide behavior against aggression. however (i.e., ants obviously have a much larger This would give them a P0 rating if it were not for survival spectrum as compared to plants at regu- the chemical and/or thorn defenses most plants lar time scales) we believe that such a labeling employ, which raises them to a P1.5 protective scheme will be more than sufficient for compari- rating. Such labels are chosen within a particular son purposes. MAP space relative to other creatures measured, and so the metrics are broad values that are 5.3. Survival signatures somewhat subjective until a sufficient database has been established. As the resolution on The volume inside a survival triangle could be biomorph-like metrics can be made fairly fine calculated to generate a single survival vector but this would be a poor scale for two reasons; one, It is possible that two creatures could have the same scale value though they might have radically dif- ferent survival spectra; two, some creatures (like the shellfish) have a bizarre metric where all survival vectors are shared within a single design feature. As shellfish use their shells for protec- tion, feeding, and (in some species) propulsion, any triangle placed upon the MAP space can be rotated uniformly between survival axes, resulting

amic in the circular survival metric shown. Shellfish MAP space is thus indistinct, but shows how

f MAP diagrams are useful for detailing a broad range of genotypes. bff A survival signature can be calculated, how- ever, if we assume higherarchy of weights for each of the MAP scales roughly proportional to their importance. To keep the resulting signature Fig. 9. Truncated MAP core for simple organisms. linear (despite their exponential implementation B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 159

complexity), we assign M = 3, A--2, and P = 1. The equation is: Survival Signature Space (SSS) = 3 x M.metric + 2 x A.metric + P.metric So a survival signature for an ant would be 13.5. For creatures with distinct MAP metrics, this signature is fairly accurate. For more indistinct creatures like the shellfish, further study is neces- sary. Fortunately as this system has been devised to measure our pseudo-linear biomorphic de- vices, this measure has shown itself to be quite adequate. By convention, when MAP values are between states they are represented by a multiple of quar- ter vector lengths. This provides sufficient resolu- tion to describe a creatures' ability without being absurd. An example would be the motion vector (Mx) for a toaster If the toaster is a standard Fig. 11. MAP space for 3 biomorphic walkers as compared to a garden ant. one, we apply a motion force that it eventually returns by release of a spring, thus rating it at M-0.5. If we had a "soft-touch" toaster that used understandable and is a design ideal our mecha- a motor triggered by pressing an electronic but- nisms aspire to, at least for the present. As an ton, we could assign it an M-0.25 rating, as the explanation of the ant metric, M2.5 refers to the mechanism is using some sort of "smarts" to obey ant's ability to handle 2-dimensional travel with our command. Thi,; is obviously higher than the ease, though ants can handle three dimensional standard mechanical model, but below the M0 terrains just short of jumping (2.75), which is just rating, as we had to begin the action externally. If short of flying (3.0). A2 refers to the individual however, the toaster is defective, so application ant's ability to ingest, process, and store hive of force yields little return (i.e., stuck toast), the sugars for fuel. It does not refer to the ant's motion metric drops to M-0.75. This leaves only participation in the hives collective ability to pro- the M-1.0 or M- metric to describe toasters cess foraged food. Many ants do not eat the where no matter how energetically you pump the foodstuffs they find, only return it to the colony lever, you'll be eating cold cereal that morning. where it is converted into manna that the ants As we generally assume biomorphs to have a ingest easily. As such, individual ants only eat and greater survival signature than a toaster (SSS = store their food, they do not "hunt" the manna -3.5), the detail region within the energy thresh- anymore than humans hunt a loaf of bread, so old can be shrunk to a point. This gives a reason- they only rate a second order acquisition metric. able resolution to the third survival exponent and The protection metric P2 refers to the ants sim- increases the resolution for any displayed metrics. ple tactics of either flight from an unknown en- An example MAP space, showing the survival emy, or fight by charging opponents it is chemi- spaces for the walkers previously described as cally adverse to. compared to a common garden ant is shown in It is interesting to note that an ant colony Fig. 11. The Spyder metric is not shown as its (considered as a single organism) would have a indistinct space ha,; yet to be classified. larger survival space for it gains from the emer- The common garden ant metric (M2.5 A2 P2.5) gent properties of massed individual efforts, but is a measure against which we compare biomorph that will have to wait for another paper. Right designs because it Jis commonly recognized, easily now, we have a tool and examples against which 160 B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

we can justify the survival success for the 70 or so almost an equivalent Turbot survival space. Full mechanical biomorphic designs currently under details will be included in future papers. study. The designs discussed so far rate as fol- lows: 5. 4. Neural morphology

"Turtle" M2.25 A- P1.5, SSS = 6.25 For biomorphs past a certain level of complex- "Lobster" M2.25 A- P2.25, SSS=7 ity, intelligence emerges as a collective effect by "Walkman" M2.5 A-0.5 P2.0, SSS=8.25 interacting with complex environments. We now "Spyder" (approximately 4.5) look at design constraints and advantages to opti- mize our designs. The most successful biologic survival tactic, But taking the many devices so far devised breeding, cannot be used for machines because of (some of which are shown in the next section) we their chemical makeup and the incredible ener- can make a complexity/survival graph as illus- gies necessary for the task. Fortunately for this trated in Fig. 12, which shows the evolutionary argument, we assume a human as a machine's progress so far attained. way of making another machine. The qualifier for Complete biomorphic device details are not this is that anyone who makes copies of the same included here because many devices have not yet machine is just a reproductive mechanism, undergone their final phenotype modifications, whereas anyone who builds a new machine as an but also because this is a paper, not a book. Most improvement on a previous machine "genotype" solar-powered biomorph devices will improve can be considered a force of directed evolution based upon the rate of new, applicable tech- for that species. niques, and their comparable survival abilities. As When a machine breaks it effectively dies, so can be seen, microcore designs improve survival another aspect of the CA design structure is to characteristics, peaking at Walkman-Solar with build robots that have a significantly long life

• - Turbots • Turbot 2 12 • - Rovers n • [] Walkman-solar O - Flowers [] - Jumpers 10 I - Walkers ~ BEAMANT • hive cluster • U Walkman 8 • [] BEAMANT SSS 00 hopper [] Turtle 6 @0 • • O Utriped • OO [] Microcore ¢IDeoeo • = nitewalker Spyder I N l I biped I Spyder []0 • • [] "Horse" 0 T°°l I I I I I I I I 1 2 3 4 6 8 10 12 14 16 Complexity (Neural components) Fig. 12. Survival signatures versus complexity for 57 active biomorph devices. B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 161 span. This is useful as survivalist elements can be observed and studied over a long time scale, and I Sene,or Systems against newer generations of biomorphic life. ! I CognitiveProcessor lofyand I There are three general classes of biomorph (Brain) table design; invertebrates, vertebrates, and coopera- I tive organisms. I ReticularCortex Invertebrates represent clusters of quasi-inde- (Hindbrain) pendent mechanisms within a single mobile chas- ! sis. Relationships between these sub-elements NervousSystem range from tenuou,; to direct electrical and me- ! chanical linkages, resulting in low element count Biomechanlcs but high survival indexes. A modular diagram is

detailed in Fig. 13. Fig. 14. Vertebrate control structure. These are the least developed of the biomorph designs so far because they are the most counter- intuitive. They will be the subject of future papers Vertebrates are structured around a concen- as soon as a wider machine spectrum has been tric spine through which sensor, power and other built and studied. Though the continuously run- information flows, usually in a top down hierar- ning Robot JurassJic Park (where most devices chy, and in a bilateral arrangement. Vertebrates built so far are continuously interacting) has had use their topological advantages to synchronize a few surprises, none was so obvious as the 4 actions between actuators (i.e., drive motors) and transistor "Turbot 2" (M2.75 A3 P2, SSS = 16.25) sometimes sensors. All biomorph walkers, with which exhibits aggressive phototropism to the the exception of microcore Spyder, work from point where it will systematically try every way to subsets of this arrangement. (See Fig. 14.) get over a significant obstacle to a brighter light In biomorphic walkers, the most successful ar- environment. It has. no focusing apparatus, yet in rangement has been to design from the mechan- a general lighted environment it exhibits strong ics back. As nature has proven time and time phototaxis. It is a two-neuron creature in a capa- again, good controllers never make up for inade- ble, point symmetric body, and is so far the quate mechanics, but knowing at least the net- undisputed "robotus-rex" amongst its weaker work properties that will control our creatures cousins. Turbots are the subject of ongoing re- allows us to make broad assumptions about the search, and amazingly capable for an invertebrate mechanics we employ. Biomorphic design, be- design. cause of the flexibility of the controller, allows for asymmetrical structures that most synchronized controllers would not tolerate. This is a major advantage in device construction as designers can build devices with vastly different leg styles, bal- Sensor Systems ance centers, and suspension on the same chassis and still expect to get an efficient convergent solution. Also, asymmetrical designs are much more interesting, easier to build, and there is I Nervous/reactionIndividual centers experimental evidence they can be inherently self-stabilizing. Vertebrates are interesting from a biomorphic I view because not all morphic layers are necessary Biomechanics to make a sufficient design. Mechanics and a nervous system have been shown, by experimen- Fig. 13. Invertebrate control structure. tal evidence, to be enough. Anything beyond this 162 B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

basic core enhances the design's survival space, because it requires a large array of diverse ma- but is optional baggage. This is seen in biological chines and the space to allow them to interact. So examples in that most life forms survive quite far there are only 60 or so working agents ranging well with a lot fewer neurons than there are from rovers, walkers, jumpers, spinners, and tum- transistors in a pocket radio. The implication is blers under study on a table the size of a standard not that designers can substitute smaller and office door. Hives exhibit greater abilities than cheaper controllers, but that survival skills can be individual elements, which is well known, but based upon much simpler precepts than world- whether this can be extended to biomorphic model symbolism. After all, the first primordial mechanisms is not clear. Biomorphs do not need creatures couldn't possibly have been a brain that to socialize for basic survival and so there has evolved a body, but the reverse, and remains so been little evolutionary force to make them do so. for the majority of all known living organisms In the Robot Jurassic Park (RJP), where over 40 today. robots of 12 different solar-powered species have We conclude that making biomorphic ma- been running continuously for over 6 months (as chines conform to anthropomorphic ideals is not of the time of this writing), there has been evi- a good idea for cases where survivability is essen- dence of flocking, fighting, cooperative group bat- tial. Robobiology can be based on some biologic tles against particularly aggressive forms, even examples (i.e., insects), but this is because insec- pecking-order dominance, but little in the way of toid life is probably the most mechanical of all true cooperation that would indicate hive struc- life forms, not the other way around (an example ture stability for such devices. It is suspected that of anti-anthropomorphology). further work will have to be done in sensor tech- nology so that like creatures would be able to 5.5. Experimental methodology recognize others of their own hive. A major lesson from the park is that among The final biomorph form, cooperative organ- different, selfish species, cooperation is not only isms, is the most elusive of the designs to date possible, it is inevitable. This is seen repeatedly

Fig. 15. A moment in the life of the Robot Jurassic Park. B. Hasslacher, M.W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 163

as the simple, two-to-four neuron creatures in the as abstractly. Without scale invariance and modu- park exhibit a vast array of recognizable larity, extending these principles to other scales biomimetic behaviors, usually as a result of insti- would require developing new concepts, but with gation from machines of a completely different the biomorphic architecture previously described design. the transition is smooth. Fig. 15 shows 15 biomorphs in interaction, composed of BEAMANT rovers, "TURBOT" 6.1. Micron machines variants, solar walkers, and a three legged "hopper", none of which use more than two Nv The first class of thought machines, con- neurons. The two-Nv design is the minimal neces- structable with current technology, is descending sary to make a planar rover, where each neuron to a few tens of square microns. Once we see how powers a single motor in a closed chassis. The to build a simple but effective biomorphic ma- range of 2 Nv creatures developed (over 30 chine at this scale, we can discuss a further species, one of which is the vicious Turbot 2) shrinking of machines to the order of a square shows the principle, of biocognitive intelligence. micron or slightly below. This is the size of a That is, survival traits are determined by the typical cell, a few microns in diameter. At this physical structure e,f a design. A classic example scale self-assembling colonies of biomorphic ma- is evolving offset visual sensors so that pho- chines are not only practical, but desirable. totropic photovores (light-seeking light-eaters) Colonies should both self-organize physically and will not dive straight into a damaging fire, but develop collective or emergent behavior (as the circle it like a moth. loner or social creatures under study do now), So our design philosophy is to make a variety which means that the collective machine has of self-contained minimalist robots, building on properties that each modular piece does not have. advantages in design observed from each genera- These meta-scale ensembles are complete organ- tion of machine. First, we get them to survive, isms; super-machines that have many interesting later, we train them to do tasks. Right now, work properties and uses. is concentrating o11 introducing "tilebot" social The powerful tool of silicon chip technology is designs, a whole new species genotype, into the available at micron scales, and we will use it to park. How this will affect the current loner de- essentially print machines. Lithography can etch vices in constant interaction should be interest- machines in parallel quite cheaply. The simplest ing. micron scale medium is a liquid that we take to be water. Instead of a walking machine, we will design a swimming machine, again using many 6. Implications of scaling and modularity clues on how to do this effectively from biological organisms (indeed, at such scales the viscosity of Biomorphic architectures are not confined to the environment would be so high that legs, ordinary scales, and fascinating things happen transformed into cilia, may be the only practical when we consider extraordinary scales for these means of directed locomotion). The design must machines. We now focus on downscaling to mi- be both minimal and respect the constraints im- cron scales and below, to the nanoscale. At small posed by silicon fabrication on materials and geo- scales, biomorphic structures would not look like metric form. ordinary bioforms, but all the principles of Using autonomous mobile machines of biomorphic architectures can be fully used. biomorphic architecture, we construct micron size Downscaling requires two critical properties: colonies of autonomous micromachines and ex- The first is architectural scale invariance, espe- amine their self-assembling properties. Equipped cially in the use of analog computation; The with simple oscillator-driven, mechanical micro- second is system ,design modularity; embedding machined "flagella" (operating in a linear mode) the organism in StarNet fashion physically as well and a light driven power supply, these microma- 164 B. Hasslacher, M.W.. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169

chines can be used (i.e., tricked) to perform a central control; that there be enough power avail- wide variety of tasks. able to allow us to use simple thrust engines A natural mechanical drive is an oscillating etched on each tile. For this it helps to use the flap or lever, micromachined with MEMS tech- wide availability of biological cells to aid assem- nology. A hybrid assembly of the drive is attached bly. to a photocell with simple circuitry to control a The model we use is a dynamic soccer ball charge/discharge cycle. Driving power is not con- covering which takes advantage of intrinsic geom- tinuous, but uses the demonstrated strategy of etry, topology and the organic functional groups larger models of "store until able to move". The already developed in the nanoscience community biomorph would negotiate a fluid environment. A for self-assembling wires. What we are after is practical initial size is roughly 100 microns square. not a single machine (though we must start there), Initially the hybrids will have to be hand assem- because at the micron scale the biological envi- bled using STM tools, though eventually they can ronment is too harsh for a (single cell)/(single be printed. We can then study the collective function) machine organism to survive. Colonies behavior of a colony of real biomorphic machines that dynamically glue into more complex ma- as a first step toward biological hybrid ap- chines offer greater functionality and survivabil- proaches (as well as adequate simulation). The ity. advantages are threefold; the colonies can be vast Consider an isolated, roughly spherical cell. in number, the exploration area unlimited, and Using standard Euler arguments we know that a the size of the devices would mean that interac- topological sphere requires 12 pentagons and the tions could occur at far greater rates than are rest hexagons to tile it completely. We take the possible at conventional scales. pentagons as special, identifiable by their five Now split the micro machine problem into two sides and the hexagons as indistinguishable slave parts, a part concerned with dynamic parallel tiles that can provide propulsion. Now we use the self-assembly of small tiles and a part concerned same tools that self-assembling wires use - or- with propulsion and motivation of individual tiles. ganic glue, and selective functional groups to do the self-assembly. The replacement for the target 6.Z Using the cell metal or bandgap pads normally used in self-as- sembling nanowires is the cell surface itself. Se- The major problems currently blocking the lectivity of chemical groups is focused on the construction of nanorobotic devices are how to edges and surfaces of the material used which we make controlling computers that will fit in a cubic will take to be silicon (though a plastic would angstrom, and how to get the power the devices serve just as well). One uses batch chemistry to will need to work. We suggest that biomorphic attach a selective layer to one side of a tile that architectures may solve the first, and that using attaches to the surface of the cell, but allows the the respectable potential difference across biolog- tile to slide over the cell's surface. ical cell walls will provide the second. Functional groups are put on the edges of the tiles which one can imagine have several colors, 6.3. Micron machine colonies - Super machines say red-green-blue etc. Attraction occurs for like colors (red-red) and repulsion for different To self-assemble machine colonies we first colors (red-green) and various permutations of make sub micron sized silicon tiles with five and this scheme. This way we avoid immediate lock-up six sides (three sided macroscale prototypes have of the tiling and allow it to take on various been built and are under study now). We want configurations depending on what functionality them to self-assemble on a roughly two-dimen- we wish it to have. Further sorting aspects emerge sional surface with three constraints: that the as a function of the edge geometry of the tile patterns that emerge be controllable and varied; edges, as well as functions of dedicated cilia that that there be special tiles that can be used for allow the tiles to flexibly "velcro" together once B. Hasslacher, M.W. Tilden ~Robotics and Autonomous Systems 15 (1995) 143-169 165 alignment has been obtained. This again can be techniques, since cost to fabricate goes up with done with functional organic groups. continuous area and the area of these discrete This is self-assembling tiling done in parallel tiles is very small. and will work provided we do not kill the cell There are several features of these self-assem- with toxic functional groups. This will be some- bling active mosaic machines that are crucial: the what deferred, however, as the tiles themselves assembly is massively parallel, and the whole con- will each have their own marginal (possibly solar) cept scales downward to the nanoscale in a clean power source that allows them sufficient auton- way. We can simulate these devices with com- omy to survive (SSS = 11.0 assuming a 3d motility puter models, and build large scale versions in a environment), and directively self-tile. Note that simple water tank as a proof of concept. This the range of functional groups available is much work is under way. wider than that for the self-assembling wires cur- It is interesting to note that a colony of diverse rently under development since we do not require biomorphic tiles could create a space of finite conduction, but simple polar bond adhesion. A elements that organize into larger collective crea- problem for which there are many known bio- tures with a potential for tile-cluster "reproduc- chemical solutions. tion". That is, there may be tile structures that To get a machine colony instead of a tiling make copies of themselves from the suspended complex, we enable the tiles by making them tile matrix they "live" in. This is purely specula- simple biomorphic machines suspended in solu- tive but it would constitute a dynamic proof of tion. Conversion of a tile to a mosaic machine the Von Neumann self-replication principle, and needs three things, a power source, a control would lead to observed machine reproduction in mechanism, and propulsion. The architectural a safe, linear regime, rather than dangerous expo- topology for the tile would most naturally be an nential growth. If the technology can be devel- extended Turbot topology of biomorphic archi- oped, it is possible that such "breeders" might tecture, which is basically two simple chaotic os- emerge from a sufficient biomorphic tile space. cillators driving separate flagella of unequal As with similar genetic-algorithm projects, we can lengths, weakly coupled by a two-transistor neu- let the devices emerge on their own, or we can ron "brain" circuit It is the simplest multi-cellu- deliberately design them once we understand their lar machine organism with capable, complex be- behavioral characteristics (as with "game of life" havior and can be likened to a machine virus. constructs). Though such a breeding scenario Once a cell is tiled, power now comes not from sounds ideal for computer simulation, as this light, but from the considerable potential differ- paper has hopefully shown, results could come ence across the cell membrane (approximately probably much faster and more effectively if these 400mV). This can be extracted with pronged elec- tiles existed in reality. trodes that pierce and adhere to the cell mem- brane, or a redundant flagellum on our microma- 6.4. Nanoscale machines - Inside the cell chine designed for the task. Biomorphic machine colonies are suspected to Generalizing the example above we see that exhibit a wide variety of complicated emergent we can do without a cell. The cell was a conve- behaviors from simple seek and avoid, to cooper- nience put there for both an assembling surface ative tasks such as foreign body rejection, to and power; these machines will form self-organiz- super cluster colony construction. This scenario is ing colonies anyway. As we descend to 100 a case study - there is nothing present in this nanometers and below we can go inside the cell, scenario that we ,cannot do now if we wished, which has several advantages. There is abundant modulo the proper power extraction mechanism ATP in the cell and many styles of available ATP for the cell, which, though forefront, is in the engines that seek ATP gradients and use them realm of biologists. The active tiles or mosaic for locomotion. If we can find functional groups machines could be made very cheaply by standard that would selectively adhere ATP engines to a 166 B. Hasslacher, M. W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 small substrate, we solve at least the power prob- micro and nano machine colonies that will be lem. Control is more subtle since circuits become useful in other contexts. We began by a simple difficult to build as we descend in size, but a extension of current research on the self-assem- two-transistor circuit should be feasible where bly of organic wires and looked at the feasibility larger designs would not. We also need mechani- of machine colony self-assembly, descending cal flagella, which is not a problem, but an oscil- downwards in scale. The structure of individual lator driver might be hard. There may be a much machines is elementary. We use the concept of more clever way to gain functionality inside the organic glue with attractive and repulsive interac- cell using biological mechanisms. If we can do tions to do dynamic self-assembly on a surface. If this scale of reduction and reach the inside of the the surface is a membrane, we try to extract cell we have a very powerful tool; i.e., a fixed power from it. These machines could just as amount of inert, mechanical force that can be easily get power in other contexts inductively or used as either an active catalyst or suppresser. from direct contact with a power or signal bus. We use the cell to protect the colony; move freely These machines are autonomous which means within the cell; operate on or modify internal cell they require no instructions from the outside structure; gain free power from glycolytically world, but their behavior is, if not predictable, driven ATP engines. Self-assembly at this scale is bounded so that we can analyze and control them already massive: ATP engines self-assemble by effectively. They are mobile and their drivers can biology; empowered machines can self-assemble be very simple oscillators drawing little power to into mobile colonies with mechanical flagella and move mechanical flagella, which are also simple. complex but targetable behavior, depending on A Siamese-twin loose coupled architecture is very the coupling between the machine halves. rich but there are many other possible biomor- phic architectures as yet unexplored. Control cir- 6.5. Molecular self-assembly cuits as synthetic neurons, as we have shown, can be very minimal. Colonies of such machines ex- The cell-nanoscale picture would be complete hibit very complex behavior. Solutions have pre- if we could learn to self-assemble all machine sented themselves as minimal, elegant, and acces- components, including a simple neuron system. sible. It requires only a paradigm shift of the Flagella can be made from self-assembled organic "robot" concept as depicted, and researchers beams which can be made very rigid. We have willing to take up the challenge. organic staples at our command from wire re- search so we can auto-glue almost any required mechanical configuration. Simple oscillator pan- Appendix: Biomorphic SolarEngines cake motors can be made self-assembling as can capacitors for power storage. It would be even Living machines have to run from solar power. more elegant if we borrow self-assembled The problem is that conventional solar cells are nanomotors used by bacteria to drive flagella and too weak, fragile, and inefficient to provide con- an ATP based power source for them. All we tinuous energy to a motor system. A minimalist need then is the ability to make a simple self-as- biomorph needs a robotic "digestive system" sembling neuron control system. As we learn which takes what little energy solar cells put out, more about building nanomechanical structures integrates it and delivers it to a motor at semi- and self-assembling wires and components, op- regular intervals based upon light availability. The tions will become obvious that we have no access cheapest and most effective circuit used in most to now. That is a way off, but in a sense working biomorph creatures (as of the time of this writing) at our current design scale is the key to a huge is detailed in Fig. 16. variety of applications that are quite natural once (Transistors are typically a 3904 and 3906, but we come to understand such structures. for higher power designs, Q2 must be replaced We summarize some key points about such with something like cascaded 2N2222s, or high B. Hasslacher, M.W. Tilden ~Robotics and Autonomous Systems 15 (1995) 143-169 167

i Vcc impedance state so long as charge remains in >~,2mA capacitor C1. As the trigger event is dependent / upon perturbations in the transistor beta-gains PB +| along the slow C1 charge path, the Solarengine , -]/-- can be considered an effective chaotic oscillator. More so when considering variables in motor load, inertia and, of course, the variability of )clI environmental light sources. " tS The advantages of this design are small com- time ponent count and adjustability, but mostly its very high off-state impedance until tripped. This Fig. 16. Solarengine schematic (Ht - ). means that Biomorphic designs can use very small solar cell arrangements which are robust against damage. gain power transistors like a TIP 31. The zener In another form, (i.e.: with diode D1 removed) should be rated at 1 volt below the solar-cells this circuit is a basic motor neuron which ampli- maximum voltage rating to get best motor effi- fies the forward edge of input signal A into a ciency. R1 should be between lk and 18kohms, pulse of variable length t resulting in mechanical and gives more motor torque at lower values with energy as well as a signal output B to trigger less energy efficiency. The value for C1 is depen- other neurons. Considering that this impulse re- dent upon the DC motor used, but is typically sponse results in a Heavyside delay factor t which greater than 1000uF. Amorphous solar cells are can be larger or smaller than the length of the those found in most solar calculators, and are input signal A (depending upon component val- usually rated at 0.7v per individual cell segment. ues) this circuit is defined as a Heavyside Neuron The zener can be replaced by 4 or 5 diodes in (Ht). As there are two forms of this circuit (the series if necessary, but more efficient solutions one shown and it's electrical inverse), there are involve low power oscillators like digital watches. also two forms of Heavyside neuron, Ht +, and For best results, it's important that the motor be Ht-. Ht- is used more often simply because a high-efficiency type from either a radio-pager NPN transistors are electrically more capable than or a dead walkman.) PNP types (see Fig. 17). Essentially the Solarengine (Pat. #5,325,031) is This circuit is called the BEAM solarengine. I a modified SCR design with supercritical feed- developed it for the Robot Olympics, used to back. In self-triggering mode, the zener D1 starts build a solaroller device which covers a 1 meter damping at Vcc -0.7v, eventually triggering Q1 distance in pure sunlight using only a cell 2-1/2" as Vcc rises, triggering and latching Q2 into a low by 1/2". I promote it in my BEAM robotics

n bias inputs

The Heavyside Neuron (Ht+/-) delay constant is set by the sum of the external ~ bias inputs against the internal bias (t), - and determines the exclusive high-pass 1 trigger input ~ output delay (+ or - edge) on the trigger input signal. It is therefore a polarized, T digital, summing differentator. (re)set input Fig. 17. The heavyside motor neuron (Ht - ). 168 B. Hasslacher, M. W. Tilden/Robotics and Autonomous Systems 15 (1995) 143-169 package because of it's simplicity, and cheapness Intelligence Laboratory, MITAIL, A.I. Memo 864, of components. September 1985. [17] R. Brooks, Engineering approach to building complete, Is all. intelligent beings, SPIE - The International Society for Optical Engineering, Intelligent Robots and Computer Vi- sion, D. Casasent, ed., Vol. 1002 (7-11 Nov., 1988) 618- 625. References [18] R. Brooks, The Whole Iguana (MIT Press Robotics Sci- ence, 1989; M. Brady, ed.,) 432-456. [1] B.D.O. Anderson, Stability of control systems with multi- [19] F. 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Murthy, {3-D} bal- Complex Systems and Field Theory Groups in the Theoretical Division of ance using {2-D} algorithms? Robotics Research, the First Los Alamos National Laboratory. Int. Symposium, M. Brady and R. Paul, eds. (MIT Press, Working mainly in mathematical Cambridge, MA, 19:~4) 279-301. physics, especially quantum field the- [47] M.H. Raibert and J.K. Hodgins, Biped gymnastics, The ory and dynamical systems, he is one of the creators of lattice gas models in International Journal of Robotics Research 9 (2) (1990) statistical mechanics. Recent interests center on lattice gas 115-132. models for novel nanoscale computation, statistical mechanics [48] M.H. Raibert, Legged robots, Communications of the of self-assembly, nonlinear dynamics of fundamental biochem- ACM 29 (6) (1986) 499-514. ical pathways, theory of biomorphic machines, and topics in the intersection between modern mathematics and theoretical [49] M.H. Raibert, Legged Robots that Balance (MIT Press, physics. He is also a visiting member in the Mathematics Cambridge, MA, 1986). Department, University of California, San Diego. [50] P. Rapp et al., Experimental studies of chaotic neural Behavior: cellular activity and electroencephalographic signals, Lecture Notes in Biomathematics 66 (1985) 175- Mark Tilden was born in Stroud, 205. England in 1961 and moved to Canada [51] E. Rietman, Creating Artificial Life (McGraw-Hill, Wind- at the age of two. He built his first crest, 1993) ISBN 0.-8306-4150-5. robot doll at the age of three out of wood scraps and progressed from [52] E. Rietman, Genesis Redux (McGraw-Hill, Windcrest, there to a Meccano suit of armor for 1994) ISBN 0-8306-4503-9. the family cat at the age of six. He [53] J. Rosenblatt and D. Payton, A fine-grained alternative built device after device through grade to the subsumption architecture for mobile robot Con- and high school winning numerous science fairs before attending the trol, Proc. Int. Joint Conf. on Neural Networks, Vol. 2 University of Waterloo in Systems (June 1989) 317-323. Engineering. Finishing with his Mas- [54] K. Shuuji and T. Kazuo, Study of dynamic biped locomo- ters, he worked for the Math Depart- tion on rugged terrain - derivation and application of the ment of that University for 7 years as a conventional robotics engineer before landing work as a robobiologist in the Physics linear inverted pendulum mode, 1991 IEEE Int. Conf. on Department at Los Alamos National Labaratory, advancing Robotics and Automation. studies on survivalist biomorphic robots.