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11/04/2021
Stein Variational Probabilistic Roadmaps
Efficient and reliable generation of global path plans are necessary for...
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04/11/2021
Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning
Sampling-based motion planners rely on incremental densification to disc...
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02/27/2020
Posterior Sampling for Anytime Motion Planning on Graphs with Expensive-to-Evaluate Edges
Collision checking is a computational bottleneck in motion planning, req...
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02/07/2020
Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement Learning with Clairvoyant Experts
Informed and robust decision making in the face of uncertainty is critic...
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10/24/2018
Sample-Efficient Learning of Nonprehensile Manipulation Policies via Physics-Based Informed State Distributions
This paper proposes a sample-efficient yet simple approach to learning c...
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10/06/2018
Bayes-CPACE: PAC Optimal Exploration in Continuous Space Bayes-Adaptive Markov Decision Processes
We present the first PAC optimal algorithm for Bayes-Adaptive Markov Dec...
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10/01/2018