Title:
Composable Optimization for Robotic Motion Planning and Control
Composable Optimization for Robotic Motion Planning and Control
Author(s)
Manchester, Zachary
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Abstract
Contact interactions are pervasive in key real-world robotic 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, 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 problems involving discontinuous, unplanned, and uncertain contact mechanics.
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Date Issued
2022-11-02
Extent
54:45 minutes
Resource Type
Moving Image
Resource Subtype
Lecture