• Corpus ID: 249097785

An Anytime Hierarchical Approach for Stochastic Task and Motion Planning

@inproceedings{Shah2021AnAH,
  title={An Anytime Hierarchical Approach for Stochastic Task and Motion Planning},
  author={Naman Shah and Siddharth Srivastava},
  year={2021}
}
In order to solve complex, long-horizon tasks, intelligent robots need 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 can be inexecutable. These problems are exacerbated in stochastic situations where the robot needs to reason about, and plan for multiple contingencies. We present a new approach for integrated task and motion planning in stochastic settings. In… 

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