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What is it that makes movement around obstacles hard? The answer seems clear: obstacles contort the geometry of the workspace and make it difficult to leverage what we consider easy and intuitive straight-line Cartesian geometry. But is Cartesian motion actually easy? It's certainly well-understood and has numerous applications. But beneath the details of linear algebra and pseudoinverses, lies a...
Many controlled systems must operate over a range of external conditions. In this paper, we focus on the problem of learning a policy to adapt a system's controller based on the value of these external conditions in order to always perform well (i.e., maximize system output). In addition, we are concerned with systems for which it is expensive to run experiments, and therefore restrict the number...
Goal sets are omnipresent in manipulation: picking up objects, placing them on counters or in bins, handing them off — all of these tasks encompass continuous sets of goals. This paper describes how to design optimal trajectories that exploit goal sets. We extend CHOMP (Covariant Hamiltonian Optimization for Motion Planning), a recent trajectory optimizer that has proven effective on high-dimensional...
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