Distributed Control of Multirobot Sweep Coverage Over a Region With Unknown Workload Distribution

In this article, we consider the problem of using a multirobot system to conduct sweep coverage over a region with uneven and unknown workload distribution. Uneven workload distribution means that a robot has to spend different amounts of time covering a unit area at different locations in the region. Unknown workload distribution means that the amount of workload at any location is unknown prior to the operation, hence online sensing and allocation of workload is needed for better efficiency. In this work, we adopt the formulation in which the entire region is separated into multiple stripes, and a discrete-time distributed workload allocation algorithm is used to allocate workload on a stripe to each robot. Previous works that adopt similar formulations do not provide rigorous stability analysis and experimental verification and lack consideration of practical aspects, such as limited sensor range. This work addresses these weaknesses and bridges the gap between theory and practice. First, compared with the existing works, the convergence of the distributed workload allocation algorithm to the optimal workload assignment is established under a more realistic assumption, and less conservative error bounds are derived, which serve as a better indicator of the effectiveness of the algorithm. Second, we propose a new algorithm that addresses the limited sensor range of robots, which is an important constraint in applications, such as agricultural spraying and building inspection. The stability analysis and error bound of the proposed algorithm are also provided. Third, realistic simulations and actual flight experiments using unmanned aerial vehicles are carried out to demonstrate the practicality and validate the theoretical results. [Video]