Robust Side Following Robotic Wheelchair by Using Homotopy Class of Human Intention

Abstract

A side-by-side following robot can alleviate the need for wheelchair pushing, thereby reducing the burden on caregivers and porters. Existing works on side-by-side following cannot be easily adapted to different environments as they either need prior knowledge about the human's path or the robot may take a different path than the human when moving around obstacles. In this work, we propose a side-by-side following system that ensures that the wheelchair takes the same path as the human around obstacles while avoiding them by leveraging the homotopy class of the human's intended path within a shared control framework. Our system can also be easily deployed in various real-world environments as it only needs prior knowledge of the human's final goal. Through quantitative experiments in simulation, we show that our method can perform significantly better compared to a baseline approach that does not leverage the knowledge of the human's intended path. We further validate our method through testing with human subjects using real robotic wheelchair. Our results show higher preference for our method as compared to the baseline method.