Sander Tonkens

University of California San Diego, Stanford University

Papers

Total Citations

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About

Sander Tonkens is a researcher advancing the frontier of safety-critical control and soft robotics. His work centers on developing rigorous, scalable methods to ensure the safe operation of autonomous systems, particularly when dealing with complex, nonlinear dynamics. A major contribution is his refinement of Control Barrier Functions (CBFs) through the lens of Hamilton-Jacobi (HJ) reachability analysis. This approach, detailed in his highly cited 2022 paper (28 citations), bridges two powerful frameworks to create more robust safety filters, addressing fundamental limitations in existing CBF methods for real-world deployment. In the domain of soft robotics, Tonkens tackles the challenge of optimal control for highly deformable systems. His 2021 work on using reduced-order finite element models enables efficient trajectory optimization for these compliant robots, a critical step toward realizing their potential in dynamic tasks. By combining theoretical rigor with practical control solutions, Tonkens is making significant strides in ensuring that next-generation autonomous and soft robotic systems are both capable and safe.