Behavior learning/operating module for mobile robots

Wai Keung Fung; Yun Hui Liu

doi:10.1109/IROS.1998.724870

Behavior learning/operating module for mobile robots

Wai Keung Fung^*, Yun Hui Liu

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

Abstract

Robot behavior learning is an emerging research topic in robotics. By incorporating learning capability to robots, engineers are not required to hard-code appropriate actions under every possible situation. Actually, this is an impossible task. In this paper, an architecture of Behavior Learning/Operating Module (BLOM) for a robot system is proposed. In the BLOM architecture, several categories of situations and actions are formed and mappings among the situation and action categories are established. A Knight Tournament (KT) strategy is proposed for adaptive categorization of situation and action patterns in learning. A computer simulation on learning a robot behavior is also presented.

Original language	English
Pages	1879-1884
Number of pages	6
DOIs	https://doi.org/10.1109/IROS.1998.724870
Publication status	Published - 1998
Externally published	Yes
Event	Proceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 1 (of 3) - Victoria, Can Duration: 13 Oct 1998 → 17 Oct 1998

Conference

Conference	Proceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Part 1 (of 3)
City	Victoria, Can
Period	13/10/98 → 17/10/98

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10.1109/IROS.1998.724870

Cite this

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abstract = "Robot behavior learning is an emerging research topic in robotics. By incorporating learning capability to robots, engineers are not required to hard-code appropriate actions under every possible situation. Actually, this is an impossible task. In this paper, an architecture of Behavior Learning/Operating Module (BLOM) for a robot system is proposed. In the BLOM architecture, several categories of situations and actions are formed and mappings among the situation and action categories are established. A Knight Tournament (KT) strategy is proposed for adaptive categorization of situation and action patterns in learning. A computer simulation on learning a robot behavior is also presented.",

author = "Fung, {Wai Keung} and Liu, {Yun Hui}",

year = "1998",

doi = "10.1109/IROS.1998.724870",

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Behavior learning/operating module for mobile robots

Abstract

Conference

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