Philipp Braun

Universität Hamburg, Australian National University

Papers

Total Citations

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About

Philipp Braun is a robotics researcher focused on safe and reliable autonomous navigation, particularly for mobile robots operating in complex, cluttered environments. His work centers on control theory, obstacle avoidance, and trajectory planning, with a strong emphasis on Lyapunov-based methods that guarantee both safety and convergence. Braun’s most notable contribution is an augmented obstacle avoidance controller for unicycle robots that is only activated in a defined “eye-shaped” neighborhood around obstacles, providing formal avoidance guarantees while remaining minimally invasive to existing tracking controllers. This work has garnered early citations for its practical, provably safe approach. He has also conducted comparative analyses of local trajectory planning algorithms within the ROS 2 ecosystem—including Dynamic Window Approach, Model Predictive Path Integral, and Regulated Pure Pursuit—offering valuable insights for real-time navigation in unpredictable industrial settings. His research bridges theoretical control design and real-world deployment, addressing the fundamental challenge of balancing safety and performance in nonlinear robotic systems. With a growing portfolio of work from 2021 to 2025, Braun is establishing himself as a contributor to the next generation of robust, guarantee-driven robot navigation.