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The Triangle of Life: Evolving Robots in Real-Time and Real-Space A.E

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The Triangle of Life: Evolving Robots in Real-Time and Real-Space A.E The Triangle of Life: Evolving Robots in Real-time and Real-space A.E. Eiben1, N. Bredeche2;3, M. Hoogendoorn1, J. Stradner4, J. Timmis5, A.M. Tyrrell6, A. Winfield7 1VU University Amsterdam ([email protected], [email protected]) 2UPMC Univ Paris 06, UMR 7222, ISIR, F-75005, Paris, France ([email protected]) 3CNRS, UMR 7222, ISIR, F-75005, Paris, France 4Karl-Franzens University Graz ([email protected]) 5University of York (jon.timmis, [email protected]) 6Bristol Robotics Lab, (alan.winfi[email protected]) Abstract organism) and vice versa. In the traditional setting, being aggregated is a transient state that enables the robots to meet Evolutionary robotics is heading towards fully embodied evo- a certain challenge after which they can disassemble and re- lution in real-time and real-space. In this paper we introduce turn to normal. In contrast, we perceive being aggregated the Triangle of Life, a generic conceptual framework for such systems in which robots can actually reproduce. This frame- as a permanent state and consider aggregated structures as work can be instantiated with different hardware approaches viable robotic organisms with the ability to reproduce. That and different reproduction mechanisms, but in all cases the is, two or more organisms can recombine the (genetic) code system revolves around the conception of a new robot organ- that specifies their makeup and initiate the creation of a new ism. The other components of the Triangle capture the prin- robotic organism. This differs from earlier work aiming at cipal stages of such a system; the Triangle as a whole serves self-replication self-reconfiguration as a guide for realizing this anticipated breakthrough and and in that a ‘child or- building systems where robot morphologies and controllers ganism’ is neither a replica of its parents, nor is it a recon- can evolve in real-time and real-space. After discussing this figured version of one of them. framework and the corresponding vision, we present a case This paper has a twofold objective, 1) to present the Tri- study using the SYMBRION research project that realized angle of Life as a conceptual framework for creating ALife some fragments of such a system in modular robot hardware. of this type and 2) to illustrate how the components of this framework can be implemented in practice. To this end, we Introduction will use the SYMBRION research project1 as a case study, even though originally the project only targeted traditional Evolutionary robotics is heading towards fully embodied swarm-to-organism-to-swarm systems, cf. Levi and Kern- evolution in real-time and real-space. In this paper we in- bach (2010). troduce the Triangle of Life, a general conceptual frame- work that can help build systems where robots can actually reproduce. The framework can be instantiated with differ- Background and related work ent hardware approaches and different reproduction mecha- The ideas in this paper can be considered from three per- nisms. For example, one could use classic mechatronic com- spectives, that of artificial life, evolutionary computing, and ponents and 3D-printing to produce new robots, or a stock (evolutionary) robotics. The modern scientific vision of cre- of autonomous actuated robot modules as raw material and ating artificial life has a long history dating back to the 1987 self-driven aggregation to implement ‘birth’. Santa Fe workshop, cf. Langdon (1989); Levy (1992); Lang- The novelty of this framework lies in the pivotal role of ton (1995). The most prominent streams in the develop- reproduction and conception. The life cycle it captures does ment of the field are traditionally based on wetware (biology not run from birth to death, but from conception to concep- and/or chemistry), software (i.e., computer simulations), and tion and it is repeated in real hardware thus creating ‘robot hardware (that is, robots). In this paper we focus on the third children’ over and over again. This is new in evolved 3D option. The main contribution of the paper from this per- printed robots, where the body structure is printed off-line. spective is the introduction of a new, integrative framework, Even if the design is evolved, the printer only produces the the Triangle of Life, that helps develop and study hardware- end result after evolution is halted (in simulation), whereas based ALife systems. In fact, the Triangle of Life defines a in our framework printing=birth, thus being part of the evo- new category of ALife systems and outlines an interesting lutionary process, rather than following it. avenue for future research. Our approach is also new in self-assembling robot swarms, because existing work traditionally focusses on the 1EU Grant number FP7-ICT-2007.8.2, running between 2008- transition of a swarm into an aggregated structure (a robot 2013. ing nor controller, so were not self-contained autonomous General robots. Only the robot’s physical morphology was evolved. conceptual The use of Lego has featured in evolutionary robot hard- framework ware. Although not evolving complete Lego robots work has described, and indeed attempted to formalise the use of Lego structures for evolution. For example Funes and Pollack Based on Based Possible (1997) describe the simulated evolution, then construction modular on 3D . robo5cs prinng instan5aons using Lego, of physical bridge-like structures. Peysakhov et al. (2000) present a graph grammar for representing and evolving Lego assemblies, and Devert et al. (2006) describe BlindBuilder, an encoding scheme for evolving Lego-like Case study Component 1 Component x structures. in SYMBRION . in SYMBRION Notably Lund (2003) describes the “Building Brains and Bodies approach” and demonstrates the co-evolution of a Lego robot body and its controller in which the evolved Figure 1: Positioning the Triangle of Life, its possible in- robot is physically constructed and tested. Here simulated stantiations in general, and the specific examples used in this evolution explores a robot body space with 3 different wheel paper. types, 25 possible wheel positions and 11 sensor positions. Lund observes that although the body search space is small, with 825 possible solutions, the search space is actually From an evolutionary perspective the framework we ad- much larger when taking into account the co-evolved con- vocate here corresponds to a major transition from evolu- troller parameters. This work is significant because it is, to tionary computing (i.e., artificial evolution in software) to the best of our knowledge, the only example to date of the Embodied Artificial Evolution (i.e., artificial evolution in simulated co-evolution, then physical realisation, of body hardware) as introduced in Eiben et al. (2012). The roadmap morphology and controller for a complete autonomous mo- outlined there considers embodiment in the broad sense, bile robot. including biochemical approaches and treats mechatronics Work by Zykov et al. (2007) describes an evolving mod- based embodied evolution as one of the possible incarna- ular robotic system on the Molecube platform. In this work, tions. The work presented here represents the first detailed self-reproduction is not a necessary prerequisite of evolu- elaboration entirely devoted to that kind of systems. tion, but rather its target. In particular, the authors evolve Finally, the vision behind this paper can also be consid- self-replicators by employing a genetic algorithm (in a 2D ered from the perspective of robotics. The relevant subarea simulation) where the measured amount of self-replication here is evolutionary robotics that has a large body of related is used as an explicit fitness criterion to evaluate morpholo- work, e.g., Nolfi and Floreano (2000); Wang et al. (2006); gies. Then, in a second stage they evolve a command se- Trianni (2008). However, most existing systems in this field quence, i.e., controller, that enables a given morphology to are based on simulations and use evolutionary algorithms as produce an identical copy of itself. However, as yet, there is optimizers in an off-line fashion, during design time. Fur- still no work that has fully demonstrates the online evolution thermore, evolution is usually applied to optimize/design of both structure and function of a modular robotic system, some parts of the robot morphology or the controller, but that is fully embodied in the modules themselves. rarely both of them. In contrast, our vision concerns real A related area with practical relevance to our vision is that hardware, on-line evolution during run time, and it includes of self-organizing robotic systems, Murata and Kurokawa the evolution of both the morphologies and the controllers. (2012). Modular self-reconfigurable robot systems, cf. Yim In the system we envision, new robots are produced contin- et al. (2007), are particularly interesting because they con- uously only limited by the availability of the raw materials stitute one of the possible technologies for implementing the and the capacity of the ‘birth’ mechanism. In the resulting Triangle of Life as shown in Figure 1. However, conceptu- system evolution is not a simple optimizer of some robot ally such systems are quite different from ours, because the features, but a force of continuous and pervasive adaptation. emphasis is on self-reconfiguring morphologies to adapt to In the landmark Golem project Lipson and Pollack (2000) dynamic environments, whereas in our evolutionary system, evolved robots capable of moving themselves across a flat new morphologies appear through ‘birth’ and adaptation of surface; robots were evolved in simulation and the fittest morphologies takes place over generations. individuals then fabricated by first 3D printing the struc- tural components then adding motors to actuate the robot. The Triangle of Life Although a remarkable achievement, the artificial creatures Throughout this paper we will not attempt to (re)define what evolved then physically realized contained neither sens- life is.
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