2019
DOI: 10.48550/arxiv.1904.13006
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Anytime Integrated Task and Motion Policies for Stochastic Environments

Abstract: In order to solve complex, long-horizon tasks, intelligent robots need to be able to carry out high-level, abstract planning and reasoning in conjunction with motion planning. However, abstract models are typically lossy and plans or policies computed using them are often unexecutable in practice. These problems are aggravated in more realistic situations with stochastic dynamics, where the robot needs to reason about, and plan for multiple possible contingencies.We present a new approach for integrated task a… Show more

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