원문정보
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초록
영어
To achieve efficient search performance for the multi-robot system which carries out the goal search task with consideration of timeliness, a multi-robot collaborative path planning system is designed to guide the robots during the search process. In the system, a planning method based on an Improved Ant Colony Optimization (IACO) algorithm is proposed. In the solution procedure, the path cost and goal timeliness are taken as two optimization goals. Compared to the traditional optimization algorithm, the IACO algorithm has global superiority which brings about better solution. Experiment results show that all robots accomplish the search task safely and efficiently by collaborative work using the proposed approach.
목차
Abstract
1. Introduction
2. System Architecture
2.1. Task Allocation Layer
2.2. Path Planning Layer
2.3. Collaboration Control Layer
3. Algorithm
3.1. Mathematical Model
3.2. IACO Algorithm
4. Experiment
4.1. Algorithm Test
4.2. Multi-robot System Test
5. Conclusion
Acknowledgements
References
1. Introduction
2. System Architecture
2.1. Task Allocation Layer
2.2. Path Planning Layer
2.3. Collaboration Control Layer
3. Algorithm
3.1. Mathematical Model
3.2. IACO Algorithm
4. Experiment
4.1. Algorithm Test
4.2. Multi-robot System Test
5. Conclusion
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보