Abstract
This paper addresses the task-oriented group generation problem for performing cooperative tasks by robot swarms. In detail, given task conditions such as the number of robot required, how can a swarm of heterogeneous robots create individual groups corresponding to desired tasks through consensus? As the solution approach, we propose a decentralized task-oriented group generation strategy, which is composed of group consensus and self-adjustment algorithms. The group consensus algorithm enables robots to select a leader robot and generate each group based on the leader. Through the self-adjustment algorithm, to meet assigned task conditions, the leader attempts to recruit more members or any robots are dismissed against the group. By doing this, robots can organize their group according to the task conditions. Extensive simulations are performed to verify that the proposed algorithms effect a computational efficient and adjustable self-organization.
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