Abstract
It is difficult for swarm robots to allocate tasks efficiently by self-organization in a dynamic unknown environment. The computational cost of swarm robots will be significantly increased for large-scale tasks, and the unbalanced task allocation of robots will also lead to a decrease in system efficiency. To address these issues, we propose a dynamic task allocation method of swarm robots based on optimal mass transport theory. The problem of large-scale tasks is solved by grouping swarm robots to complete regional tasks. The task reallocation mechanism realizes the balanced task allocation of individual robots. This paper solves the symmetric assignment between robot and task and between the robot groups and the regional tasks. Our simulation and experimental results demonstrate that the proposed method can make the swarm robots self-organize to allocate large-scale dynamic tasks effectively. The tasks can also be balanced allocated to each robot in the swarm of robots.
Highlights
Swarm robotics has been defined as “the study of how large numbers of relatively simple physically embodied agents can be designed such that a desired collective behavior emerges from the local interactions among agents and between the agents and the environment” [1]
This paper proposes a task allocation method based on the optimal mass transport theory in the dynamic environment
Task allocation methods of swarm robots are mainly divided into the centralized method and distributed method
Summary
Swarm robotics has been defined as “the study of how large numbers of relatively simple physically embodied agents can be designed such that a desired collective behavior emerges from the local interactions among agents and between the agents and the environment” [1]. Task allocation of the swarm robotic system has the following main challenges:. In the dynamic task environment, the pre-determined task allocation strategy will limit the optimization of resources and reduce the task’s efficiency to complete, so it is challenging to make adaptive adjustment of task allocation on time in the unknown task environment. This paper proposes a task allocation method based on the optimal mass transport theory in the dynamic environment. The Optimal Mass Transport formulation is tailored for the dynamic task allocation of the swarm robots in the unknown environment.
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