Autonomous Living Machines
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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.