A waypoint navigation method with collision avoidance using an artificial potential method on random priority

摘要

This paper proposes a waypoint navigation method with collision avoidance using an artificial potential method on random priority. To establish a multi-robot navigation system that consists of various tasks, the navigation system needs to avoid collisions by communicating with each robot path on-site. Robots have an autopilot system that includes waypoint navigation, but using this navigation method to avoid collisions is more difficult than using entire path planning. For waypoint-based path planning, we proposed a novel waypoint correction method using the artificial potential method with random priority. In addition to that, we proposed a speeding up algorithm for the artificial potential method with k-nearest neighbor and Delaunay triangulation. Our experimental results show that using random priority is sufficient to provide over 80% improvement to reach the desired speed, and the proposed random priority is similar to using general wireless conditions such as slotted ALOHA.