Adaptive controller for biped robot mimicking human gait

This thesis presents a novel adaptive approach to teach the biped humanoid robot to ambulate through human imitation. For this purpose a human body motion capturing system is developed using tri-axis accelerometers (attached to human legs and torso). The tilt angle patterns information from the human is transformed to control and teach various ambulatory skills for humanoid robot bipedalism. Lyapunov stability based model reference adaptive controller (MRAC) technique is implemented to address the poorly known actuator dynamical characteristics and unpredictable variations of the biped system. Theoratical and practical methods are developed for biped walking and substantiated by computer simulations and real-time experiments under Matlab/Simulink environment. Design implementation and experimental results are presented in this document.