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Evolutionary robotics—A review

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Abstract

In evolutionary robotics, a suitable robot control system is developed automatically through evolution due to the interactions between the robot and its environment. It is a complicated task, as the robot and the environment constitute a highly dynamical system. Several methods have been tried by various investigators to solve this problem. This paper provides a survey on some of these important studies carried out in the recent past.

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References

  • Baluja S 1996 Evolution of an artificial neural network based autonomous land vehicle controller.IEEE Trans. Syst., Man Cybern. B26: 450–63

    Google Scholar 

  • Beer R D, Gallagher J C 1992 Evolving dynamic neural networks for adaptive behaviour.Adaptive Behav. 1: 91–122

    Article  Google Scholar 

  • Brooks R A 1986 A robust layered control system for a mobile robot.IEEE J. Robot. Autom. 2: 14–23

    MathSciNet  Google Scholar 

  • Colombetti M, Dorigo M 1993 Learning to control an autonomous robot by distributed genetic algorithms. InProc. of the Second International Conference on Simulation of Adaptive behaviour: From Animals to Animats 2, (eds) J Meyer, Roitblat, S W Wilson (Cambridge, MA: MIT Press/Bradford)

    Google Scholar 

  • Dorigo M 1993 Genetic and non-genetic operators in ALECSYS.Evolut. Comput. 1: 151–164

    Google Scholar 

  • Floreano D, Mondada F 1994 Automatic creation of an autonomous agent: Genetic evolution of a neural network driven robot. InFrom Animals to Animats 3: Proceedings of Third Conference on Simulation of Adaptive behaviour, (eds) D Cliff, P Husbands, J Meyer, S W Wilson (Cambridge, MA: MIT Press/Bradford)

    Google Scholar 

  • Floreano D, Mondada F 1996 Evolution of homing navigation in a real mobile robot.IEEE Trans. Syst. Man, Cybern., 26: 396–07

    Article  Google Scholar 

  • Galt S, Luk B L, Collie A A 1997 Evolution of smooth and efficient walking motions for an 8-legged robot.Proc. of the Sixth European Workshop on Learning Robots, Brighton, UK

  • Goldberg D E 1989Genetic algorithms in search, optimization and machine learning. (Reading, MA: Addison-Wesley)

    MATH  Google Scholar 

  • Gomi T, Ide K 1997 Emergence of gaits of a legged robot by collaboration through evolution.Proc. of the International Symposium on Artificial Life and Robotics (Springer Verlag)

  • Grefenstette J, Cobb H C 1991 User’s guide for SAMUEL (NRL Memorandum Report 6820). Washington, DC: Naval Research Laboratory, USA

    Google Scholar 

  • Grefenstette J, Schultz A 1994 An evolutionary approach to learning in robots.Proc. of the Machine Learning Workshop on Robot Learning, New Brunswick, NJ

  • Gruau F, Quatramaran K 1997 Cellular encoding for interactive evolutionary robotics. InProc. of Fourth European Conference on Artificial Life, (eds) P Husbands, I Harvey (Cambridge, MA: MIT Press/Bradford)

    Google Scholar 

  • Harvey I 1992 Species adaptation genetic algorithms: The basis for a continuing SAGA. InProc. of the First European Conference on Artificial Life, (eds) F Varela, P Bourgine (Cambridge, MA: MIT Press/Bradford) pp 346–354

    Google Scholar 

  • Harvey I, Husbands P, Cliff D 1994 Seeing the light: Artificial evolution, real vision. InProc. of the Third International Conference on Simulation of Adaptive behaviour: From Animals to Animats 3, (eds) D Cliff, P Husbands, J Meyer, S W Wilson (Cambridge, MA: MIT Press/Bradford)

    Google Scholar 

  • Harvey I, Husbands P, Cliff D, Thompson A, Jakobi N 1997 Evolutionary robotics: The Sussex approach.Robotics Autonomous Syst. 20: 205–224

    Article  Google Scholar 

  • Holland J H 1975Adaptation in natural and artificial systems (Ann Arbor, MI: University of Michigan Press)

    Google Scholar 

  • Husbands P, Harvey I, Cliff D, Miller G 1997 Artificial evolution: A new path for AI?Brain Cogn. 34: 130–159

    Article  Google Scholar 

  • Jakobi N 1997a Half-baked, ad-hoc and noisy: Minimal simulations for evolutionary robotics. InProc. 4th Eur. Conf. on Artificial Life (eds) P Husbands, I Harvey (Cambridge, MA: MIT Press/Bradford Books)

    Google Scholar 

  • Jakobi N 1997b Evolutionary robotics and the radical envelope of noise hypothesis.Adaptive Behav. 6: 131–174

    Article  Google Scholar 

  • Jeong I K, Lee J J 1997 Evolving cooperative mobile robots using a modified genetic algorithm.Robotics Autonomous Syst. 21: 197–205

    Article  Google Scholar 

  • Kosko B 1994Neural networks and fuzzy systems (New Delhi: Prentice-Hall)

    Google Scholar 

  • Koza J 1992Genetic programming (Cambridge MA: MIT Press)

    MATH  Google Scholar 

  • Lee W P, Hallam J, Lund H H 1997a Applying genetic programming to evolve behaviour primitives and arbitrators for mobile robots.Proc. of IEEE 4th Int. Conf. on Evolutionary Computation (Piscataway, NJ)

  • Lee W P, Hallam J, Lund H H 1997b Learning complex robot behaviours by evolutionary approaches.Proc. of the Sixth European Workshop on Learning Robots, (Heidelberg: Springer Verlag)

    Google Scholar 

  • Lund H H, Miglino O 1996 From simulated to real robots.Proc. of the Third IEEE International Conference on Evolutionary Computation (IEEE Computer Society Press)

  • Meeden L A 1996 An incremental approach to developing intelligent neural network controllers for robots.IEEE Trans. Syst., Man Cyber. B26: 474–485

    Article  Google Scholar 

  • Miglino O, Nafasi K, Taylor C 1994 Selection for wandering behaviour in a small robot. Technical Report: UCLA-CRSP-94-01, Department of Cognitive Science, University of California, Los Angeles, CA

    Google Scholar 

  • Miglino O, Lund H H, Nolfi S 1995 Evolving mobile robots in simulated and real environments.Artif. Life 2: 417–434

    Article  Google Scholar 

  • Mondada F, Franzi E, Ienne P 1993 Mobile robot miniaturization: A tool for investigation in control algorithms.Proc. 3rd Int. Symp. on Experimental Robotics, Kyoto, Japan

  • Nolfi S 1996 Evolving non-trivial behaviours on real robots: a garbage collecting robot. Technical Report, Institute of Psychology, CNR, Rome

    Google Scholar 

  • Nolfi S 1997a Using emergent modularity to develop control systems for mobile robots.Adaptive Behav. 5: 343–363

    Article  Google Scholar 

  • Nolfi S 1997b Evolving non-trivial behaviour on autonomous robots: Adaptation is more powerful than decomposition and integration. InEvolutionary robotics: From intelligent robots to artificial life (ER’97) (ed.) T Gomi (AAI Books)

  • Nolfi S 1997c Evolving non-trivial behaviours on real robots: A garbage collecting robot.Robotics Autonomous Syst. 22: 187–198

    Article  Google Scholar 

  • Nolfi S, Parisi D 1995 Evolving non-trivial behaviours on real robots: an autonomous robot that picks up objects. InProc. 4th Congress of the Italian Association for Artificial Intelligence (eds) Gori, Soda (Springer)

  • Nolfi S, Miglino O, Parisi D 1994 Phenotypic plasticity in evolving neural networks: Evolving the control system for an autonomous agent. Technical Report: PCIA-94-04, Institute of Psychology, CNR, Rome

    Google Scholar 

  • Nordin P, Banzhaf W 1996 An on-line method to evolve behaviour and to control a miniature robot in real time with genetic programming.Adaptive Behav. 5: 107–140

    Article  Google Scholar 

  • Pratihar D K, Deb K, Ghosh A 1999a A genetic-fuzzy approach for mobile robot navigation among moving obstacles.Int. J. Approximate Reasoning 20: 145–172

    Article  MATH  Google Scholar 

  • Pratihar D K, Deb K, Ghosh A 1999b Design of a genetic-fuzzy system for planning crab gaits of a six-legged robot.J. Comput. Info. Technol. (special issue on Evolutionary Computation) 7: 93–101

    Google Scholar 

  • Pratihar D K, Deb K, Ghosh A 2000 Optimal turning gait of a six-legged robot using a GA-fuzzy approach.Artificial intelligence for engineering design, analysis and manufacturing — AIEDAM 14: 207–219

    Google Scholar 

  • Pratihar D K, Hayashida N, Takagi H 2001 Comparison of mapping methods to visualize the EC landscape.Proc. of the Fifth Int. Conf. on knowledge-based intelligent information engineering systems & allied technologies, KES’2001, Nara, Japan, pp 223–227

  • Ram A, Arkin R, Boone G, Pearce M 1994 Using genetic algorithms to learn reactive control parameters for autonomous robot navigation.Adaptive Behav. 2: 277–305

    Article  Google Scholar 

  • Reynolds C 1993 An evolved, vision-based model of obstacle avoidance behaviour. InArtificial Life III, Santa Fe Institute Studies in the Sciences of Complexity, Proceedings (ed.) C Langton (Reading, MA: Addison Wesley) vol. 16

    Google Scholar 

  • Schwefel H P 1995Evolution and optimum seeking (New York: Wiley)

    Google Scholar 

  • Salomon R 1996 Increasing adaptivity through evolution strategies. Maes, InProc. 4th Int. Conf. on Simulation of Adaptive behaviour: From Animals to Animats 4 (eds) P Maes, M J Mataric, J A Meyer, J Pollack, S W Wilson (Cambridge, MA: MIT Press/Bradford Books)

    Google Scholar 

  • Smith T 1997Adding vision to Khepera: An autonomous robot footballer. Master’s thesis, School of Cognitive and Computing Sciences, University of Sussex

Download references

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  1. Department of Mechanical Engineering, Indian Institute of Technology, 721 302, Kharagpur, India

    Dilip Kumar Pratihar

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  1. Dilip Kumar Pratihar
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Pratihar, D.K. Evolutionary robotics—A review. Sadhana 28, 999–1009 (2003). https://doi.org/10.1007/BF02703810

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  • DOI: https://doi.org/10.1007/BF02703810

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