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Equitable Workload Partitioning for Multi-Robot Exploration through Pairwise Optimization

Klodt, Lukas and Willert, Volker (2015):
Equitable Workload Partitioning for Multi-Robot Exploration through Pairwise Optimization.
In: IEEE International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, Sep 28 - Oct 02, [Conference or Workshop Item]

Abstract

One of the main challenges when using multiple robots to explore unknown environments is the allocation of target points or regions to the individual units. To date, commonly used approaches produce uneven assignment of targets in situations where multiple targets have to be assigned to each robot. This imbalance can lead to increased overall exploration time and poses an interesting task for further investigation. Based on insights from Multi-Robot Routing and Traveling Salesman Problem research, we propose a specific algorithm for target point allocation that has advantageous properties in highly dynamic applications like exploration. The presented pairwise optimization procedure is suitable for application in distributed and challenging settings, not requiring central coordination or all to all communication, making our exploration strategy robust and flexible. We provide a theoretical analysis and statistical evaluations. Comparisons with representative approaches from the literature show that our algorithm is competitive with the best performing centralized approach.

Item Type: Conference or Workshop Item
Erschienen: 2015
Creators: Klodt, Lukas and Willert, Volker
Title: Equitable Workload Partitioning for Multi-Robot Exploration through Pairwise Optimization
Language: English
Abstract:

One of the main challenges when using multiple robots to explore unknown environments is the allocation of target points or regions to the individual units. To date, commonly used approaches produce uneven assignment of targets in situations where multiple targets have to be assigned to each robot. This imbalance can lead to increased overall exploration time and poses an interesting task for further investigation. Based on insights from Multi-Robot Routing and Traveling Salesman Problem research, we propose a specific algorithm for target point allocation that has advantageous properties in highly dynamic applications like exploration. The presented pairwise optimization procedure is suitable for application in distributed and challenging settings, not requiring central coordination or all to all communication, making our exploration strategy robust and flexible. We provide a theoretical analysis and statistical evaluations. Comparisons with representative approaches from the literature show that our algorithm is competitive with the best performing centralized approach.

Journal or Publication Title: Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS)
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik
18 Department of Electrical Engineering and Information Technology
Event Title: IEEE International Conference on Intelligent Robots and Systems (IROS)
Event Location: Hamburg, Germany
Event Dates: Sep 28 - Oct 02
Date Deposited: 06 Oct 2015 08:17
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