Paper Info
Title
Selection of two arm-swing strategies for bipedal walking to enhance both stability and efficiency.
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.
Year
DOI
Venue
2016
10.1080/01691864.2015.1135079
ADVANCED ROBOTICS
Keywords
Field
DocType
Humanoid robots,falling risk,arm swing,bipedal walking,selection of locomotion
Control theory,Selection algorithm,Model predictive control,Control engineering,Engineering,Robot,Trajectory,Internal model,Humanoid robot,Center of gravity,Swing
Journal
Volume
Issue
ISSN
30.0
6
0169-1864
Citations 
PageRank 
References 
0
0.34
13
Authors
5
Name
Order
Citations
PageRank
Kobayashi, T.162.26
Kosuke Sekiyama229658.93
Tadayoshi Aoyama36928.58
Yasuhisa Hasegawa445694.62
Toshio Fukuda52723818.58