A Herd Foraging-Based Adaptive Coverage Path Planning in Unbounded Environments
Junqi Zhang, Peng Zu, MengChu Zhou · 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) · 2022
Coverage path planning is important in helping us perform such tasks as map construction and criminal capture. As an outstanding method, predator-prey coverage path planning employs a predator-prey mechanism to enable a robot to adaptively cover an arbitrary 2-D surface with dynamic obastacles. However, it is designed for bounded environments only and cannot work in unbounded environments. Inspired by the foraging behavior of herds in nature, this work proposes an adaptive coverage path planning algorithm suitable for unbounded environments, called herd foraging-based coverage path planning. It employs a virtual herd to control the overall coverage direction of a robot, allowing it to be applied in unbounded environments. The experimental results demonstrate its effectiveness in unbounded environments.