A control framework for autonomous e-scooters. Issue 2 (2021) - Soloperto, Raffaele; Wenzelburger, Philipp; Meister, David; Scheuble, Dominik; Breidohr, Veronika S.M.; Allgöwer, Frank
Abstract: In this paper, we address the core challenges of self-stabilization, obstacle detection, and collision avoidance arising when developing autonomous electric scooters for sharing systems. In particular, we firstly demonstrate how an e-scooter can balance itself by the usage of a reaction wheel combined with a braking mechanism. Secondly, we show how a depth-camera can be utilized to generate a grid map representation of the environment surrounding the e-scooter and how this can be used to design a computationally tractable algorithm which ensures obstacle avoidance as well as path following. Finally, the goal of this paper is to provide a starting point for the development of autonomous e-scooters for sharing systems by combining approaches from various research communities in a common application framework.