Biped Locomotion using CPG with Sensory Interaction

This article presents the design and analysis of a controller based on a biologically inspired central pattern generator (CPC) network of mutually coupled Matsuoka nonlinear oscillators to generate adaptive rhythmic human like movement for biped robots.. The paper focuses on the way in which the sensory signals feedback contribute to generate dynamic, stable and sustained rhythmic movements with robust gaits for biped robots. In addition, the paper shows how the driving input and external perturbation affect the speed of locomotion and change the period of its own active phase. The new design was studied through interaction between simulated interconnection coupling dynamics with 6 links and a musculoskeletal model with 6 degrees of freedom (DOFs) of a biped robot. The robot used the weighted outputs of mutually inhibited oscillators as torques to actuate its joints. The implemented model helps to realize the interaction between the controller, the mechanism of the robot, and the environment. In addition, it helps to study the necessary conditions for efficient generation of stable rhythmic walking at different speed, on different type of terrains and robustness in response to disturbances. Evaluations of the developed CPG based adaptive bipedal locomotion are carried out through simulations with successful testing results.