Robust Perception Skills for Autonomous Elevator Operation by Mobile Robots

Abstract

Autonomous mobile service robots with transportation tasks are often restricted to work on a single floor, since remote access to elevators is expensive to integrate for reasons of safety certification. Therefore, already ten years ago first robots have been enabled to use the human interface for riding an elevator. This requires a variety of perception and manipulation capabilities as well as social skills when it comes to interaction with other people who want to use the elevator too. We summarize the progress in solving the specific tasks of detecting and localizing the required buttons to press robustly. A deep-learning approach for detecting buttons in images is combined with a verification based on predefined knowledge on button arrangements in the elevator's control panels. Also perception of the elevator's state and our realization of the robot's elevator riding capabilities are discussed.