[2512.19576] LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller

Computer Science > Robotics arXiv:2512.19576 (cs) [Submitted on 22 Dec 2025 (v1), last revised 31 Mar 2026 (this version, v4)] Title:LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller Authors:Kirill Djebko, Tom Baumann, Erik Dilger, Frank Puppe, Sergio Montenegro View a PDF of the paper titled LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller, by Kirill Djebko and Tom Baumann and Erik Dilger and Frank Puppe and Sergio Montenegro View PDF HTML (experimental) Abstract:Attitude control is essential for many satellite missions. Classical controllers, however, are time-consuming to design and sensitive to model uncertainties and variations in operational boundary conditions. Deep Reinforcement Learning (DRL) offers a promising alternative by learning adaptive control strategies through autonomous interaction with a simulation environment. Overcoming the Sim2Real gap, which involves deploying an agent trained in simulation onto the real physical satellite, remains a significant challenge. In this work, we present the first successful in-orbit demonstration of an AI-based attitude controller for inertial pointing maneuvers. The controller was trained entirely in simulation and deployed to the InnoCube 3U nanosatellite, which was developed by the Julius-Maximilians-Universität Würzburg in cooperation with the Technische Universität Berlin, and launched in January 2025. We present the AI agent design, the methodol...