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Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning


Apr 11, 2021
Aditya Mandalika, Rosario Scalise, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa

* Submitted to IROS 2021 

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Posterior Sampling for Anytime Motion Planning on Graphs with Expensive-to-Evaluate Edges


Mar 20, 2020
Brian Hou, Sanjiban Choudhury, Gilwoo Lee, Aditya Mandalika, Siddhartha S. Srinivasa

* ICRA 2020 

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LEGO: Leveraging Experience in Roadmap Generation for Sampling-Based Planning


Jul 22, 2019
Rahul Kumar, Aditya Mandalika, Sanjiban Choudhury, Siddhartha S. Srinivasa

* Accepted at International Conference on Intelligent Robots and Systems (IROS) 2019 

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Generalized Lazy Search for Robot Motion Planning: Interleaving Search and Edge Evaluation via Event-based Toggles


Apr 08, 2019
Aditya Mandalika, Sanjiban Choudhury, Oren Salzman, Siddhartha Srinivasa

* Submitted to International Conference on Automated Planning and Scheduling (ICAPS) 2019 

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Sample-Efficient Learning of Nonprehensile Manipulation Policies via Physics-Based Informed State Distributions


Oct 24, 2018
Lerrel Pinto, Aditya Mandalika, Brian Hou, Siddhartha Srinivasa


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Bayesian Policy Optimization for Model Uncertainty


Oct 01, 2018
Gilwoo Lee, Brian Hou, Aditya Mandalika, Jeongseok Lee, Siddhartha S. Srinivasa


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Lazy Receding Horizon A* for Efficient Path Planning in Graphs with Expensive-to-Evaluate Edges


Mar 15, 2018
Aditya Mandalika, Oren Salzman, Siddhartha Srinivasa

* 16 pages; typos corrected; revised text; results unchanged 

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