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Journal of Information Science and Engineering, Vol. 30 No. 3, pp. 637-652 (May 2014)


Multi-Step Learning to Search for Dynamic Environment Navigation*


CHUNG-CHE YU1 AND CHIEH-CHIH WANG1,2
1Graduate Institute of Networking and Multimedia
2Department of Computer Science and Information Engineering
National Taiwan University
Taipei, 116 Taiwan
E-mail: fish60@robotics.csie.ntu.edu.tw; bobwang@ntu.edu.tw

While navigation could be done using existing rule-based approaches, it becomes more attractive to use learning from demonstration (LfD) approaches to ease the burden of tedious rule designing and parameter tuning procedures. In our previous work, navigation in simple dynamic environments is achieved using the Learning to Search (LEARCH) algorithm with a proper feature set and the proposed data set refinement procedure. In this paper, the multi-step learning approach with goal-related information is proposed to further capture the successive motion behavior of the user in complex environments. The behaviors of the demonstrator could be matched by the motion control module in which policies of the demonstrator are well captured.

Keywords: learning from demonstration, robot navigation, dynamic environments, learning to search, motion behavior learning

Full Text () Retrieve PDF document (201405_06.pdf)

Received February 28, 2013; accepted June 15, 2013.
Communicated by Hung-Yu Kao, Tzung-Pei Hong, Takahira Yamaguchi, Yau-Hwang Kuo, and Vincent Shin- Mu Tseng.
* This work was supported in part by National Science Council, National Taiwan University and Intel Corporation under Grants NSC 100-2221-E-002-238-MY2, NSC 102-2221-E-002-179, NSC 100-2911-I-002-001, and 101R7501.