Collision Avoidance for Mobile Robots Using Proximity Sensors

Tang, Y.; Mamaev, I.; Alagi, H.; Abel, B.; Hein, B.

Due to the rise of e-commerce material handling industry has been experiencing significant changes, especially in the COVID-19 pandemic. Notwithstanding the broad utilization of Automated Guided Vehicles (AGVs) for many years, the demand for Autonomous Mobile Robot (AMR) is rapidly increasing. One of the main challenges in autonomous operation in an unstructured environment is gapless perception. In this paper, we present a concept for reactive collision avoidance using Capacitive Proximity Sensor (CPS), with the goal to augment robot perception in close proximity situations. We propose a proximity-based potential field method using capacitive measurement for collision avoidance. A local minima problem is solved by applying tangential forces around the virtual obstacle points. We evaluate the proof-of-concept both in simulation and on a real mobile robot equipped with CPS. The results have shown that capacitive sensing technology can compensate localization tolerance and odometry drift closing the perception gap in close proximity scenarios. © 2021, Springer Nature Switzerland AG.