Andreas Lawitzky

Technical University of Munich, Institute of Automation

Papers

Total Citations

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About

Andreas Lawitzky is a researcher whose work lies at the intersection of robotics safety and autonomous navigation. His key contributions focus on developing rigorous, provably safe motion planning algorithms for mobile robots. Lawitzky’s most impactful work, “Determining states of inevitable collision using reachability analysis” (2014, 24 citations), introduces a powerful theoretical framework that guarantees robot safety without sacrificing navigational flexibility. By leveraging reachable set theory, this approach identifies all states from which a collision is unavoidable, enabling robots to operate with maximum autonomy while maintaining a formal safety guarantee—a critical advancement for real-world deployment. Earlier, Lawitzky extended the classic Dynamic Window Approach to accommodate omni-directional robots with polygonal shapes (2011, 6 citations), providing a more general and robust solution for reactive collision avoidance. This work improved upon prior implementations and demonstrated practical success. Through these contributions, Lawitzky has advanced the field’s ability to design robots that are both agile and certifiably safe, making his research essential reading for anyone working on autonomous navigation, motion planning, or safety-critical robotics systems.