Autonomous docking and charging is a core capability for any mobile robot. Today, this typically involves navigating the robot close to the charging station and using laser scanner data with contour-matching techniques to detect the charger’s position and dock using dedicated control algorithms.
To take this a step further, we are joining hands with Fraunhofer IPA on a “Quick Check” project to explore a smarter and more resilient approach. The goal of this study is to investigate how semantic maps can be combined with SLAM technology to improve docking robustness and efficiency. In addition, we are exploring the use of a language model (LLM) that enables the robot to understand simple voice commands such as “drive to charge” and execute them autonomously.
Our sincere thanks to the Ministerium für Wirtschaft, Arbeit und Tourismus Baden-Württemberg (Baden-Württemberg Ministry of Economic Affairs, Labour and Tourism) and the KI-Fortschrittszentrum supporting this project.
SmartCharge
