A Knowledge Base for Dynamic Path Planning for Multi-Agents
| Authors: | Kwak Nosan, Seoul National University, Korea, Republic of
Ji Sanghoon, Seoul National University, Korea, Republic of
Lee Beomhee, Seoul National University, Korea, Republic of |
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| Topic: | 4.3 Robotics |
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| Session: | Multi-Robot Systems |
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| Keywords: | Fuzzy control, Genetic algorithms, Path planning, Mobile robots |
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Abstract
A fuzzy rule base is proposed to navigate multi-agents from initial positions to target positions in unknown environments. The proposed fuzzy rule base determines the highest priority of nine possible heading directions. The fuzzy rule base has been developed employing genetic algorithms as an approach to dynamic path planning of autonomous multi-agents in unknown environments. Paths which satisfy some optimization criteria with respect to moving distance, smoothness, and clearance of obstacles was obtained from the fuzzy rule base. The fuzzy rule base was obtained from off-line navigation with precise sensor modeling and applied to various simulated on-line navigation. The performance of the fuzzy rule base in different unknown environments is acceptable and shown in simulation results.
