Selection of two arm-swing strategies for bipedal walking to enhance both stability and efficiency. (18th March 2016) - Kobayashi, Taisuke; Sekiyama, Kosuke; Aoyama, Tadayoshi; Hasegawa, Yasuhisa; Fukuda, Toshio
Abstract : Walking ability, which involves mainly stability and efficiency, is one of the most important issues in humanoid robots. Effective use of a robot's arms is expected to improve its walking ability under its body constraints. Although several types of arm-swing strategies have been proposed, they are difficult to execute simultaneously. We propose two-stage integration of these strategies to enhance both stability and efficiency. A selection algorithm for locomotion (SAL) selects the appropriate strategy according to the demands of the situation. In the first stage, two strategies are evaluated. One of them, Ro-SAL, entails use and compensation of the moment of the swing leg by hip rotation and arm swing. The other strategy, Su-SAL, entails the support of center of gravity trajectory tracking based on a predictive control. Ro-SAL is effective for the stable state and states with internal model error, whereas Su-SAL is effective in states with external force and environmental complexity. In the second stage of the proposed method (AS-SAL), the robot recognizes the current state and selects the optimal combination of the two arm-swing strategies. As a result, a humanoid robot can exhibit more efficient, stable bipedal walking without falling. Graphical Abstract: