Compliance Control for Biped Walking on Rough Terrain

In this paper, we propose a control system that changes the compliance based on the walking speed to stabilize biped walking on rough terrain. The proposed system changes walking modes depends on its walking speed. In the downhill terrain, when the walking speed increases, the stiffness of the ankle in the support phase is controlled so as to brake the increased speed. In the uphill terrain, when the walking speed decreases, the stiffness of the waist joint is controlled and the desired trajectory for the supported leg is shifted so as not to falls down backward. To validate the efficiency of the proposed system, the stability of walking with the proposed system is examined in the two dimensional dynamics simulation. It is shown that the robot with the proposed system can walk in the more variable rough terrain and with the broader walking speed than without changing the stiffness of the joints.

[1]  Akio Ishiguro,et al.  Enhancing Stability of a Passive Dynamic Running Biped by Exploiting a Nonlinear Spring , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Masaki Ogino,et al.  Stabilization of quasi-passive pneumatic muscle walker , 2004, 4th IEEE/RAS International Conference on Humanoid Robots, 2004..

[3]  Atsuo Takanishi,et al.  Development of foot system of biped walking robot capable of maintaining four-point contact , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  T. McMahon,et al.  Ballistic walking. , 1980, Journal of biomechanics.

[5]  Atsuo Takanishi,et al.  Development of a dynamic biped walking system for humanoid - development of a biped walking robot adapting to the humans' living floor , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[6]  Gentaro Taga,et al.  A model of the neuro-musculo-skeletal system for human locomotion , 1995, Biological Cybernetics.

[7]  Masaki Ogino,et al.  Learning Energy-Efficient Walking with Ballistic Walking , 2006 .

[8]  Hiroshi Kimura,et al.  Adaptive Motion of Animals and Machines , 2005 .