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Distributed Hedonic Coalition Formation for Multi-Robot Task Allocation
In this paper, we study the problem of allocating multiple heterogeneous robots to tasks. Due to the limited capabilities of the robots, a task might need more than one robot to complete it. The fundamental problem of optimally partitioning the set of n robots into m disjoint coalitions for allocati...
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Main Authors: | , , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | In this paper, we study the problem of allocating multiple heterogeneous robots to tasks. Due to the limited capabilities of the robots, a task might need more than one robot to complete it. The fundamental problem of optimally partitioning the set of n robots into m disjoint coalitions for allocating to m tasks is proven to be NP-hard. To solve this computationally intractable problem, we propose a distributed hedonic game formulation, where each robot decides to join or not join a team based on the other robots allocated to that particular task. It uses a bipartite matching technique to establish an initial set of coalitions before letting the robots coordinate asynchronously and change teams if desired. Our proposed solution is proved to converge to a Nash-stable solution. Results show that our proposed approach is fast and handles asynchronous robot-to-robot communication while earning more utility (up to 23%) than an existing technique in the majority of the test cases. |
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ISSN: | 2161-8089 |
DOI: | 10.1109/CASE49439.2021.9551582 |