Minimum Displacement Motion Planning for Movable Obstacles

Author:

Thomas Antony,Mastrogiovanni Fulvio

Publisher

Springer Nature Switzerland

Reference21 articles.

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2. Dantam, N.T., Kingston, Z.K., Chaudhuri, S., Kavraki, L.E.: Incremental task and motion planning: a constraint-based approach. In: Robotics: Science and Systems (2016)

3. Dogar, M., Srinivasa, S.: A framework for push-grasping in clutter. In: Robotics: Science and Systems VII (2011)

4. Domahidi, A., Jerez, J.: Forces Professional. Embotech AG. https://embotech.com/FORCES-Pro (2014–2019)

5. Garrett, C.R., Lozano-Perez, T., Kaelbling, L.P.: FFRob: leveraging symbolic planning for efficient task and motion planning. Int. J. Rob. Res. 37(1), 104–136 (2018)

Cited by 2 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. Navigation Among Movable Obstacles Using Machine Learning Based Total Time Cost Optimization;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

2. Computational Tradeoff in Minimum Obstacle Displacement Planning for Robot Navigation;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

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