Biological systems such as birds and humans are able to move with great agility, efficiency, and robustness in a wide range of environments. Endowing machines with similar capabilities requires designing controllers that address the challenges of high-degree-of-freedom, high-degree-of-underactuation, nonlinear & hybrid dynamics, as well as input, state, and safety-critical constraints in the presence of model and sensing uncertainty. In this talk, I will present the design of planning and control algorithms for (i) dynamic legged locomotion over discrete terrain that requires enforcing safety-critical constraints in the form of precise foot placements; and (ii) dynamic aerial manipulation through cooperative transportation of a cable-suspended payload using multiple aerial robots with safety-critical constraints on manifolds. We will use the tools of control Lyapunov and control barrier functions for enforcing stability and safety while combining it with deep learning for visual perception.
Speaker: Koushil Sreenath, UC Berkeley
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