Structural Evolution of Central Pattern Generators for Bipedal Walking in 3D Simulation

Anthropomorphic walking for a simulated bipedal robot has been realized by means of artificial evolution of central pattern generator (CPG) networks. The approach has been investigated through full rigid-body dynamics simulations in 3D of a bipedal robot with 14 degrees of freedom. The half-center CPG model has been used as an oscillator unit, with interconnection paths between oscillators undergoing structural modifications using a genetic algorithm. In addition, the connection weights in a feedback network of predefined structure were evolved. Furthermore, a supporting structure was added to the robot in order to guide the evolutionary process towards natural, human-like gaits. Subsequently, this structure was removed, and the ability of the best evolved controller to generate a bipedal gait without the help of the supporting structure was verified. Stable, natural gait patterns were obtained, with a maximum walking speed of around 0.9 m/s.

[1]  Hiroshi Shimizu,et al.  Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment , 1991, Biological Cybernetics.

[2]  Phil Husbands,et al.  Evolution of central pattern generators for bipedal walking in a real-time physics environment , 2002, IEEE Trans. Evol. Comput..

[3]  G. Taga Nonlinear Dynamics of the Human Motor Control-Real-Time and Anticipatory Adaptation of Locomotion and Development of Movements - , 2000 .

[4]  Shinya Aoi,et al.  Locomotion control of a biped locomotion robot using nonlinear oscillators , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[5]  R. Brooks,et al.  The cog project: building a humanoid robot , 1999 .

[6]  Chen Jiapin,et al.  Design of central pattern generator for humanoid robot walking based on multi-objective GA , 2000 .

[7]  Hideki Kozima,et al.  An epigenetic approach to human-robot communication , 2000, Proceedings 9th IEEE International Workshop on Robot and Human Interactive Communication. IEEE RO-MAN 2000 (Cat. No.00TH8499).

[8]  Örjan Ekeberg,et al.  A combined neuronal and mechanical model of fish swimming , 1993, Biological Cybernetics.

[9]  Atsuo Takanishi,et al.  REALIZATION OF DYNAMIC WALKING BY THE BIPED WALKING ROBOT WL-10RD. , 1985 .

[10]  Andrew L. Kun,et al.  Control of variable speed gaits for a biped robot , 1999, IEEE Robotics Autom. Mag..

[11]  T. Takenaka,et al.  The development of Honda humanoid robot , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[12]  T. Brown The intrinsic factors in the act of progression in the mammal , 1911 .

[13]  S. Grillner,et al.  The effect of dorsal root transection on the efferent motor pattern in the cat's hindlimb during locomotion. , 1984, Acta physiologica Scandinavica.

[14]  Hiroshi Kimura,et al.  Realization of Dynamic Walking and Running of the Quadruped Using Neural Oscillator , 1999, Auton. Robots.

[15]  Krister Wolff,et al.  Learning Biped Locomotion from First Principles on a Simulated Humanoid Robot Using Linear Genetic Programming , 2003, GECCO.

[16]  Shinya Aoi,et al.  Locomotion Control of a Biped Robot Using Nonlinear Oscillators , 2005, Auton. Robots.

[17]  T. Brown,et al.  The Factors in Rhythmic Activity of the Nervous System , 1912 .

[18]  Chandana Paul,et al.  The road less travelled: morphology in the optimization of biped robot locomotion , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[19]  Roy Featherstone,et al.  Robot Dynamics Algorithms , 1987 .

[20]  S. Grillner,et al.  A computer-based model for realistic simulations of neural networks. II. The segmental network generating locomotor rhythmicity in the lamprey. , 1992 .

[21]  Mattias Wahde,et al.  A flexible evolutionary method for the generation and implementation of behaviors for humanoid robots , 2001 .

[22]  Toshio Fukuda,et al.  Natural motion generation of biped locomotion robot using hierarchical trajectory generation method consisting of GA, EP layers , 1997, Proceedings of International Conference on Robotics and Automation.

[23]  Kiyotoshi Matsuoka,et al.  Mechanisms of frequency and pattern control in the neural rhythm generators , 1987, Biological Cybernetics.

[24]  E. Ott Chaos in Dynamical Systems: Contents , 1993 .

[25]  Hiroshi Ishiguro,et al.  Development of an android robot for studying human-robot interaction , 2004 .

[26]  S. Grillner,et al.  Neural networks for vertebrate locomotion. , 1996, Scientific American.

[27]  S. Grillner,et al.  Neural networks that co-ordinate locomotion and body orientation in lamprey , 1995, Trends in Neurosciences.

[28]  M.-Y. Cheng,et al.  Genetic algorithm for control design of biped locomotion , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[29]  Ralph Etienne-Cummings,et al.  CPG Design using Inhibitory Networks , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[30]  Masaki Ogino,et al.  Reinforcement learning of humanoid rhythmic walking parameters based on visual information , 2004, Adv. Robotics.

[31]  Wang,et al.  A neuromorphic controller for a three-link biped robot , 1989 .

[32]  J. Duysens,et al.  Neural control of locomotion; Part 1: The central pattern generator from cats to humans , 1998 .