Robust collaborative collision avoidance between robots with nearly symmetric crossing trajectories

Abstract

The growth in both acceptance and usage of mobile robots have given risen to novel challenges in robot navigation. Often, robots that share a space but are unable to communicate are required to safely avoid each other even under sensor noise. Current approaches have often relied on the assumption that collaboration is always done correctly, in practice, sensor noise might lead robots to make avoidance motions that are not mutually beneficial and do not actually decrease the collision risk. Our approach intends to mitigate the negative impact of sensor noise in collaborative collision avoidance of robots. As a consequence, even if robots initially take non-mutually beneficial avoidance motions they would correctly perceive their role in the next decision step.