Incremental Task and Motion Planning: A Constraint-Based Approach

Author:

T. Dantam Neil,K. Kingston Zachary,Chaudhuri Swarat,E. Kavraki Lydia

Publisher

Robotics: Science and Systems Foundation

Cited by 46 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. SR-FDIL: Synergistic Replay for Federated Domain-Incremental Learning;IEEE Transactions on Parallel and Distributed Systems;2024-11

2. R-LGP: A Reachability-guided Logic-geometric Programming Framework for Optimal Task and Motion Planning on Mobile Manipulators;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Improved M4M: Faster and Richer Planning for Manipulation Among Movable Objects in Cluttered 3D Workspaces;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. Collision-Free Target Grasping in Complex and Cluttered Environment for Efficient Task and Motion Planning;IEEE Access;2024

5. Robust planning for multi-stage forceful manipulation;The International Journal of Robotics Research;2023-12-01

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