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This work explores the use of topological tools for achieving effective non-prehensile manipulation in cluttered, constrained workspaces.
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J. Zhou, Y. Hou, and M. T. Mason, “Pushing revisited: Differential flatness, trajectory planning, and stabilization,” The International Journal of Robotics Research , vol. 38, no. 12-13, pp. 1477–1489, 2019
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J. Lee, Y. Cho, C. Nam, J. Park, and C. Kim, “Efficient obstacle rearrangement for object manipulation tasks in cluttered environments,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 183–189
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J. Varley, C. DeChant, A. Richardson, J. Ruales, and P. Allen, “Shape completion enabled robotic grasping,” in 2017 IEEE/RSJ international conference on intelligent robots and systems (IROS) . IEEE, 2017, pp. 2442–2447
2017
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W. Bejjani, R. Papallas, M. Leonetti, and M. R. Dogar, “Planning with a receding horizon for manipulation in clutter using a learned value function,” in 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) . IEEE, 2018, pp. 1–9
2018
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A. Zeng, S. Song, K.-T. Yu, E. Donlon, F. R. Hogan, M. Bauza, D. Ma, O. Taylor, M. Liu, E. Romo, et al. , “Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching,” in 2018 IEEE international conference on robotics and automation (ICRA) . IEEE, 2018, pp. 3750–3757
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P.-C. Huang and A. K. Mok, “A case study of cyber-physical system design: Autonomous pick-and-place robot,” in 2018 ieee 24th international conference on embedded and real-time computing systems and applications (rtcsa) . IEEE, 2018, pp. 22–31
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S. D. Han, N. M. Stiffler, A. Krontiris, K. E. Bekris, and J. Yu, “Complexity results and fast methods for optimal tabletop rearrangement with overhand grasps,” The International Journal of Robotics Research , vol. 37, no. 13-14, pp. 1775–1795, 2018
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W. Yuan, J. A. Stork, D. Kragic, M. Y. Wang, and K. Hang, “Rearrangement with nonprehensile manipulation using deep reinforcement learning,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 270–277
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J. Poon, Y. Cui, J. Ooga, A. Ogawa, and T. Matsubara, “Probabilistic active filtering for object search in clutter,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 7256–7261
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R. Papallas and M. R. Dogar, “Non-prehensile manipulation in clutter with human-in-the-loop,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 6723–6729
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Y. Labbé, S. Zagoruyko, I. Kalevatykh, I. Laptev, J. Carpentier, M. Aubry, and J. Sivic, “Monte-carlo tree search for efficient visually guided rearrangement planning,” IEEE Robotics and Automation Letters , vol. 5, no. 2, pp. 3715–3722, 2020
2020
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H. Song, J. A. Haustein, W. Yuan, K. Hang, M. Y. Wang, D. Kragic, and J. A. Stork, “Multi-object rearrangement with monte carlo tree search: A case study on planar nonprehensile sorting,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2020, pp. 9433–9440
2020
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2020
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R. Wang, C. Mitash, S. Lu, D. Boehm, and K. E. Bekris, “Safe and effective picking paths in clutter given discrete distributions of object poses,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2020, pp. 5715–5721
2020
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A. H. Qureshi, J. Dong, A. Choe, and M. C. Yip, “Neural manipulation planning on constraint manifolds,” IEEE Robotics and Automation Letters , vol. 5, no. 4, pp. 6089–6096, 2020
2020
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2020
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2020
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2021
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B. Huang, S. D. Han, A. Boularias, and J. Yu, “Dipn: Deep interaction prediction network with application to clutter removal,” in IEEE International Conference on Robotics and Automation , 2021
2021
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