Mees A. van Löben Sels

Robust Jumping With an Articulated Soft Quadruped Via Trajectory Optimization and Iterative Learning

Quadrupeds deployed in real-world scenarios need to be robust to unmodelled dynamic effects. In this work, we aim to increase the robustness of quadrupedal periodic forward jumping (i.e., pronking) by unifying cutting-edge model-based trajectory optimization and iterative learning control. Using a r