Max Robotics — Global Service Robot Directory + US Certification

About

Max Spahn is a robotics researcher whose work centers on real-time motion generation, trajectory optimization, and model predictive control for complex robotic systems. His major contributions lie in advancing whole-body motion planning for mobile manipulators and multi-robot systems, particularly through the development of optimization fabrics and sampling-based control methods. Spahn introduced a real-time trajectory optimization approach for coupled mobile manipulation that overcomes the limitations of decoupled base-arm planning, enabling more flexible and efficient motion in dynamic, unstructured environments. He also pioneered a sampling-based Model Predictive Path Integral (MPPI) controller that leverages GPU-parallelizable physics simulations (IsaacGym) for high-speed, realistic forward dynamics, a method that has garnered significant attention with over 17 citations since 2023. His work on dynamic optimization fabrics generalizes geometric motion generation to dynamic and nonholonomic scenarios, proving fundamental properties of the framework. Spahn has further extended these concepts to multi-robot systems and developed automated parameter tuning via Bayesian optimization. With over 78 total citations across his most-cited papers, Spahn is recognized for bridging theoretical motion planning with practical, real-time deployment, and his benchmarking suite, localPlannerBench, provides a valuable tool for the robotics community.