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Pathfinder Discovery Networks for Neural Message Passing
In this work we propose Pathfinder Discovery Networks (PDNs), a method f...
10/24/2020 ∙ by Benedek Rozemberczki, et al. ∙
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Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments
Deep reinforcement learning (RL) agents are able to learn contact-rich m...
10/22/2020 ∙ by Jun Yamada, et al. ∙
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Learning Equality Constraints for Motion Planning on Manifolds
Constrained robot motion planning is a widely used technique to solve co...
09/24/2020 ∙ by Giovanni Sutanto, et al. ∙
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Learning Manifolds for Sequential Motion Planning
Motion planning with constraints is an important part of many real-world...
06/13/2020 ∙ by Isabel M. Rayas Fernández, et al. ∙
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Sampling-Based Motion Planning on Manifold Sequences
We address the problem of planning robot motions in constrained configur...
06/03/2020 ∙ by Peter Englert, et al. ∙
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Kinematic Morphing Networks for Manipulation Skill Transfer
The transfer of a robot skill between different geometric environments i...
03/05/2018 ∙ by Peter Englert, et al. ∙
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Identification of Unmodeled Objects from Symbolic Descriptions
Successful human-robot cooperation hinges on each agent's ability to pro...
01/23/2017 ∙ by Andrea Baisero, et al. ∙
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Multi-Task Policy Search
Learning policies that generalize across multiple tasks is an important ...
07/02/2013 ∙ by Marc Peter Deisenroth, et al. ∙
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