Dynamic Task Allocation Method of Swarm Robots Based on Optimal Mass Transport Theory

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.

Optimization of Dynamic Task Allocation forMulti-UAV Systems: Search and Rescue Scenario

“…The authors in [24] proposed a method for efficient dynamic task allocation for a swarm of robots working on large-scale tasks. They used the concept of optimal mass transport theory for this purpose.…”

Dynamic and Distributed Optimization for the Allocation of Aerial Swarm Vehicles

“…Compute α xy (k + 1) using (11), for all {x, y} ∈ E and location to the other agents which requires the network to update so that other UAVs can calculate their optimal waypoint. As shown in Fig.…”

“…Optimal transport has been used for swarm guidance in [9], [10] but has yet to be used dynamically. A dynamic OT algorithm is developed in [11] but it is not distributed. Radioactivity sensing swarms refer to waypoint allocation but do not use an OT based algorithm [12], [13].…”