Composable Optimization for Robotic Motion Planning and Control
Abstract:
Contact interactions are pervasive in real-world robotics tasks like manipulation and walking. However, the non-smooth dynamics associated with impacts and friction remain challenging to model, and motion planning and control algorithms that can fluently and efficiently reason about contact remain elusive. In this talk, I will share recent work from my research group that takes an “optimization-first” approach to these challenges: collision detection, physics, motion planning, state estimation, and control are all posed as constrained optimization problems. We then build a set of algorithmic and numerical tools that allow us to flexibly compose these optimization sub-problems to solve complex robotics tasks involving discontinuous, unplanned, and uncertain contact mechanics.
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