Abstract
This paper describes how a distributed neural architecture for the general control of robots has been applied for the generation of a walking behaviour in the Aibo robotic dog. The architecture described has been already demonstrated useful for the generation of more simple behaviours like standing or standing up. This paper describes specifically how it has been applied to the generation of a walking pattern in a quadruped with twelve degrees of freedom, in both simulator and real robot.
The main target of this paper is to show that our distributed architecture can be applied to complex dynamic tasks like walking. Nevertheless, by showing this, we also show how a completely neural and distributed controller can be obtained for a robot as complex as Aibo on a task as complex as walking. This second result is by itself a new and interesting one since, to our extent, there are no other completely neural controllers for quadruped with so many DOF that allow the robot to walk.
Bio-inspiration is used in three ways: first we use the concept of central pattern generators in animals to obtain the desired walking robot. Second we apply evolutionary processes to obtain the neural controllers. Third, we seek limitations in how real dogs do walk in order to apply them to our controller and limit the search space.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Grillner, S.: Neurobiological bases of rhythmic motor acts in vertebrates. Science 228, 143–149 (1985)
Hallam, J., Ijspeert, A.: 4. In: Using evolutionary methods to parametrize neural models: a study of the lamprey central pattern generator, pp. 119–142. Physica-Verlag, Heidelberg (2003)
Ijspeert, A.J.: A connectionist central pattern generator for the aquatic and terrestrial gaits of a simulated salamander. Biological Cybernetics 84, 331–348 (2001)
Hiroshi Kimura, S.A., Sakurama, K.: Realization of dinamic walking and running of the quadruped using neural oscillator. Autonomous Robots 7(3), 247–258 (1999)
Hiroshi Kimura, Y.F., Konaga, K.: Adaptive dynamic walking of a quadruped robot by using neural system model. Advanced Robot 15, 859–876 (2001)
Collins, J., Richmond, S.: Hard-wired central pattern generators for quadrupedal locomotion. Biological Cybernetics 71, 375–385 (1994)
Téllez, R., Angulo, C.: Evolving cooperation of simple agents for the control of an autonomous robot. In: Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (2004)
Téllez, R., Angulo, C., Pardo, D.: Highly modular architecture for the general control of autonomous robots. In: Proceedings of the 8th International Work-Conference on Artificial Neural Networks (2005)
Seys, C.W., Beer, R.D.: Evolving walking: the anatomy of an evolutionary search. In: From Animals to Animats: Proceedings of the eighth international conference on simulation of adaptive behavior, vol. 8 (2004)
Mathayomchan, B., Beer, R.: Center-crossing recurrent neural networks for the evolution of rhythmic behavior. Neural Computation 14, 2043–2051 (2002)
Yong, H., Miikkulainen, R.: Cooperative coevolution of multiagent systems. Technical Report AI01-287, Department of computer sciences, University of Texas (2001)
Michel, O.: Webots: Professional mobile robot simulation. Journal of Advanced Robotics Systems 1(1), 39–42 (2004)
Minsky, M.: The Society of Mind. Touchtone Books (1988)
Carruthers, P.: The case for massively modular models of mind. In: Contemporary Debates in Cognitive Science. Blackwell, Malden (2005)
Gómez, F., Miikkulainen, R.: Solving non-markovian control tasks with neuroevolution. In: Proceedings of the IJCAI 1999 (1999)
Gomez, F., Miikkulainen, R.: Incremental evolution of complex general behavior. Technical Report AI96-248, University of Texas (1996)
Hopfield, J.: Neurons with graded response properties have collective computational properties like those of two-state neurons. Proc. National Academy of Sciences USA 81, 3088–3092 (1984)
Reeve, R.: Generating walking behaviours in legged robots. PhD thesis, University of Edinburgh (1999)
Nunamaker, D.M., Blauner, P.: Normal and abnormal gait. In: Textbook of small animal orthopaedics. International veterinary information service, USA (1985)
Ijspeert, A.: Locomotion, vertebrate. In: The handbook of brain theory and neural networks, 2nd edn., pp. 649–654 (2002)
Pollack, J.B., Hornby, G.S., Lipson, H., Funes, P.: Computer creativity in the automatic design of robots. Leonardo 36(2), 115–121 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Téllez, R.A., Angulo, C., Pardo, D.E. (2006). Evolving the Walking Behaviour of a 12 DOF Quadruped Using a Distributed Neural Architecture. In: Ijspeert, A.J., Masuzawa, T., Kusumoto, S. (eds) Biologically Inspired Approaches to Advanced Information Technology. BioADIT 2006. Lecture Notes in Computer Science, vol 3853. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11613022_4
Download citation
DOI: https://doi.org/10.1007/11613022_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31253-6
Online ISBN: 978-3-540-32438-6
eBook Packages: Computer ScienceComputer Science (R0)