Title :
Locomotion selection of Multi-Locomotion Robot based on Falling Risk and moving efficiency
Author :
Kobayashi, Taisuke ; Aoyama, Tadayoshi ; Sekiyama, Kosuke ; Lu, Zhiguo ; Hasegawa, Yasuhisa ; Fukuda, Toshio
Author_Institution :
Dept. of Mech. Eng., Nagoya Univ., Nagoya, Japan
Abstract :
This paper deals with a method of locomotion selection based on Falling Risk and moving efficiency. The robot estimates information from sensors by solving state equation. The robot evaluates the Falling Risk as an indicator of uncertainty. Falling Risk is derived from measured information by using Bayesian Network. Locomotion selection during walking is modeled as a Semi-Markov Decision Process and the most appropriate locomotion is selected by using the greedy algorithm. As a result, the robot can move in the environment that is difficult to travel by single locomotion mode, maintaining the maximum moving efficiency.
Keywords :
Bayes methods; Markov processes; decision theory; greedy algorithms; mobile robots; multi-robot systems; Bayesian network; falling risk; greedy algorithm; locomotion selection; moving efficiency; multilocomotion robot; semiMarkov decision process; state equation; Bayesian methods; Legged locomotion; Measurement by laser beam; Robot sensing systems; Uncertainty;
Conference_Titel :
Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on
Conference_Location :
Vilamoura
Print_ISBN :
978-1-4673-1737-5
DOI :
10.1109/IROS.2012.6385774
