Title :
Self-stabilized biped walking under control of a novel reflexive network
Author :
Geng, Tao ; Porr, Bernd ; Wörgötter, Florentin
Author_Institution :
Computational Neurosci., Stirling Univ., UK
Abstract :
Biologically inspired reflexive controllers have been implemented on various walking robots. However, due to the natural instability of biped walking, up to date, there has not existed a biped robot that depends exclusively on reflexive controllers for its dynamically stable walking control. In this paper, we present our design and experiments of a planar biped robot under control of a pure reflexive controller that includes only local extensor and flexor reflexes (no any other reflexes for explicit stability control). The reflexive controller is built with biologically inspired stretch receptors and model neurons. It requires fewer phasic feedbacks than those reflexive controllers of multilegged robots, and does not employ any kind of position or velocity control algorithm even on its low level. Instead, the approximate property of this reflexive controller has allowed our biped robot to substantially exploit its own passive dynamics in some stages of its walking gait cycle. Due to the interaction of the reflexive controller and the properly designed mechanics of the robot, the biped robot works as a closely coupled neuromechanical system, and demonstrates self-stabilizing property in the experiments of slightly perturbed walking, shallow slope walking, and various speed walking. Moreover, our biped robot can walk stably at a relatively high speed (nearly three leg-lengths per second). We know of no other biped robots that could attain such a high relative speed.
Keywords :
adaptive control; legged locomotion; robot dynamics; stability; biologically inspired reflexive controllers; explicit stability control; multilegged robots; neuromechanical system; reflexive controller; self-stabilized biped walking; walking gait cycle; walking robots; Biological control systems; Biological system modeling; Control systems; Legged locomotion; Mechanical factors; Neurofeedback; Neurons; Robot control; Stability; Velocity control;
Conference_Titel :
Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on
Print_ISBN :
0-7803-8912-3
DOI :
10.1109/IROS.2005.1545449