Tobias Schoels

University of Freiburg, Microsystems (United Kingdom)

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About

Tobias Schoels is a leading researcher in robotic motion planning and trajectory optimization, with a focus on safe, real-time control in dynamic environments. His work bridges the gap between theoretical optimal control and practical robotic systems, particularly in constrained and human-shared spaces. Schoels is best known for advancing direct collocation methods for trajectory optimization in constrained robotic systems, where he demonstrated how to achieve dynamically accurate trajectories while addressing significant kinematic errors—a critical challenge for robots operating under physical constraints like contact or closed-chain kinematics. His 2022 paper on this topic has garnered 42 citations, establishing a foundation for robust motion generation in complex robotic tasks. A second major contribution is the development of CIAO⁎, a Model Predictive Control (MPC)-based framework for safe motion planning in predictable dynamic environments. This work, cited 36 times, addresses the critical gap in optimization-based planning by explicitly incorporating the movement of other agents (e.g., humans or robots) to guarantee collision avoidance. Schoels’ research is highly impactful for autonomous systems operating in shared workspaces, such as collaborative manufacturing or service robotics. His achievements highlight a commitment to both theoretical rigor and practical deployment, making his work essential reading for students and researchers in robotics, control, and autonomous navigation.