(A) unified walking control framework of ankle, hip and stepping strategy based on dynamics of divergent component of motion

Abstract

It is difficult for a biped robot to stably walk in various environments or disturbances. From the observation of human, ankle, and hip strategies work in combination to recover balance, a stepping strategy is triggered by a strong disturbance. In this study, we proposed a biped walking controller that optimized three push recovery strategies: the ankle, hip, and stepping strategies. We suggested formulations that related the effects of each strategy to the stability of walking based on the Linear Inverted Pendulum with Flywheel Model (LIPFM). With these relations, we could set up an optimization problem that integrates all the strategies, including step time change. These strategies are not applied hierarchically, but applied according to each weighting factor. Various combinations of weighting factors can be used to determine how the robot should respond to an external push. The optimization problem derived here includes many non-linear components, but it has been linearized though some assumptions and it can be applied to a robot in real-time. This method is designed to be robust to modeling errors or weak perturbations, by exploiting the advantages of the foot. Hence, it is very practical to apply this algorithm to a real robot. This study also presents the design and system integration of the 13-degree-of-freedom legged platform, GAZELLE. The goal is to develop a fast and reliable biped platform for walking experiments. Rapid leg movement can increase robustness in walking stability. During external push or walking on uneven ground, fast leg movement can realize an abrupt change on the landing position. The effectiveness of the walking controller has been verified through abstracted model simulation, full dynamics simulation. The practical application of algorithm has been verified through the experiments with bipedal platform GAZELLE.