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08/07/2023
Robots as AI Double Agents: Privacy in Motion Planning
Robotics and automation are poised to change the landscape of home and w...
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07/08/2023
Meta-Policy Learning over Plan Ensembles for Robust Articulated Object Manipulation
Recent work has shown that complex manipulation skills, such as pushing ...
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03/12/2023
The Planner Optimization Problem: Formulations and Frameworks
Identifying internal parameters for planning is crucial to maximizing th...
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02/27/2023
Object Reconfiguration with Simulation-Derived Feasible Actions
3D object reconfiguration encompasses common robot manipulation tasks in...
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02/08/2023
Kinodynamic Rapidly-exploring Random Forest for Rearrangement-Based Nonprehensile Manipulation
Rearrangement-based nonprehensile manipulation still remains as a challe...
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12/06/2022
Solving Rearrangement Puzzles using Path Defragmentation in Factored State Spaces
Rearrangement puzzles are variations of rearrangement problems in which ...
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08/03/2022
Rearrangement-Based Manipulation via Kinodynamic Planning and Dynamic Planning Horizons
Robot manipulation in cluttered environments often requires complex and ...
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04/18/2022
Learning to Retrieve Relevant Experiences for Motion Planning
Recent work has demonstrated that motion planners' performance can be si...
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12/13/2021
MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets
Recently, there has been a wealth of development in motion planning for ...
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09/14/2021
Comparing Reconstruction- and Contrastive-based Models for Visual Task Planning
Learning state representations enables robotic planning directly from ra...
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04/24/2021
KDF: Kinodynamic Motion Planning via Geometric Sampling-based Algorithms and Funnel Control
We integrate sampling-based planning techniques with funnel-based feedba...
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03/23/2021
Robowflex: Robot Motion Planning with MoveIt Made Easy
Robowflex is a software library for robot motion planning in industrial ...
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02/28/2021
Path Planning for Manipulation using Experience-driven Random Trees
Robotic systems may frequently come across similar manipulation planning...
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10/29/2020
Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions
Earlier work has shown that reusing experience from prior motion plannin...
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09/23/2020
LTLf Synthesis on Probabilistic Systems
Many systems are naturally modeled as Markov Decision Processes (MDPs), ...
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09/20/2019
How Much Do Unstated Problem Constraints Limit Deep Robotic Reinforcement Learning?
Deep Reinforcement Learning is a promising paradigm for robotic control ...
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03/20/2019
Using Local Experiences for Global Motion Planning
Sampling-based planners are effective in many real-world applications su...
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01/29/2018