Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions-Reference-Cited by-同舟云学术

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Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions

Published:2021-05-30 Issue: Volume: Page:
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Container-title:2021 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Chamzas Constantinos,Kingston Zachary,Quintero-Pena Carlos,Shrivastava Anshumali,Kavraki Lydia E.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9560720/9560666/09561104.pdf?arnumber=9561104

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning Sampling Dictionaries for Efficient and Generalizable Robot Motion Planning With Transformers;IEEE Robotics and Automation Letters;2023-12

2. Motion Planning as Online Learning: A Multi-Armed Bandit Approach to Kinodynamic Sampling-Based Planning;IEEE Robotics and Automation Letters;2023-10

3. GuILD: Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

4. Motion Planning of Manipulator by Points-Guided Sampling Network;IEEE Transactions on Automation Science and Engineering;2023-04

5. Automatic Cross-domain Task Plan Transfer by Caching Abstract Skills;Algorithmic Foundations of Robotics XV;2022-12-15

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