Florian Beck

Papers

Total Citations

H-Index

About

Florian Beck is a robotics researcher specializing in model predictive control (MPC) and trajectory optimization for autonomous systems. His work focuses on enabling robots—particularly serial manipulators and uncrewed ground vehicles (UGVs)—to plan and execute complex motions in real time, bridging the gap between high-level task planning and low-level control. Beck’s major contributions include the development of **BoundMPC**, a novel joint-space MPC strategy that allows robot manipulators to follow Cartesian reference paths with guaranteed error bounds, even when handling via-points and orientation constraints. His 2024 paper on model predictive trajectory optimization with dynamically changing waypoints (13 citations) addresses a critical challenge in online motion planning: seamlessly incorporating discrete actions from superordinate task planners. Beck has also advanced shared control for UGVs, enabling semi-autonomous operation with obstacle avoidance for applications in warehouses, inspection, and search & rescue. His work is notable for systematically integrating real-time replanning with strict safety and performance guarantees, making it highly relevant for industrial and field robotics. With a rapidly growing citation record and innovations published in 2024–2025, Beck is establishing himself as a key contributor to the next generation of intelligent, reactive robotic systems.