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Objects rarely sit in isolation in everyday human environments.
A. Curtis, X. Fang, L. P. Kaelbling, T. Lozano-Pérez, and C. R. Garrett, “Long-horizon manipulation of unknown objects via task and motion planning with estimated affordances,” in 2022 International Conference on Robotics and Automation (ICRA) . IEEE, 2022, pp. 1940–1946
1946
Earlier work this paper cites.
R. E. Korf, “Depth-first iterative-deepening: An optimal admissible tree search,” Artificial intelligence , vol. 27, no. 1, pp. 97–109, 1985
1985
Earlier work this paper cites.
R. B. Rusu, Z. C. Marton, N. Blodow, M. Dolha, and M. Beetz, “Towards 3d point cloud based object maps for household environments,” Robotics and Autonomous Systems , vol. 56, no. 11, pp. 927–941, 2008. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0921889008001140
2008
Earlier work this paper cites.
A. Cosgun, T. Hermans, V. Emeli, and M. Stilman, “Push Planning for Object Placement on Cluttered Table Surfaces,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems , 11 2011. [Online]. Available: http://www.cs.utah.edu/~thermans/papers/cosgun-iros2011.pdf
2011
Earlier work this paper cites.
L. Chang, J. R. Smith, and D. Fox, “Interactive singulation of objects from a pile,” in IEEE Intl. Conf. on Robotics and Automation , 2012, pp. 3875–3882
2012
Earlier work this paper cites.
M. Gupta and G. S. Sukhatme, “Using manipulation primitives for brick sorting in clutter,” in IEEE Intl. Conf. on Robotics and Automation , 2012, pp. 3883–3889
2012
Earlier work this paper cites.
Y. Jiang, M. Lim, C. Zheng, and A. Saxena, “Learning to place new objects in a scene,” The International Journal of Robotics Research , vol. 31, no. 9, p. 1021–1043, May 2012
2012
Earlier work this paper cites.
S. Panda, A. A. Hafez, and C. Jawahar, “Learning support order for manipulation in clutter,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems , 2013, pp. 809–815
2013
Earlier work this paper cites.
A. Hornung, K. M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard, “OctoMap: An efficient probabilistic 3D mapping framework based on octrees,” Autonomous Robots , 2013, software available at http://octomap.github.com . [Online]. Available: http://octomap.github.com
2013
Earlier work this paper cites.
M. R. Dogar, M. C. Koval, A. Tallavajhula, and S. S. Srinivasa, “Object search by manipulation,” Autonomous Robots , vol. 36, no. 1-2, pp. 153–167, 2014
2014
Earlier work this paper cites.
T. Lozano-Pérez and L. P. Kaelbling, “A constraint-based method for solving sequential manipulation planning problems,” in 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2014, pp. 3684–3691
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
B. Calli, A. Singh, A. Walsman, S. Srinivasa, P. Abbeel, and A. M. Dollar, “The YCB object and model set: Towards common benchmarks for manipulation research,” in Intl. Conf. on Advanced Robotics , 2015
2015
Earlier work this paper cites.
C. R. Garrett, T. Lozano-Pérez, and L. P. Kaelbling, “Sample-based methods for factored task and motion planning.” in Robotics: Science and Systems , 2017
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” Advances in neural information processing systems , vol. 30, 2017
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
B. Kim, Z. Wang, L. P. Kaelbling, and T. Lozano-Pérez, “Learning to guide task and motion planning using score-space representation,” The International Journal of Robotics Research , vol. 38, no. 7, pp. 793–812, 2019
2019
Earlier work this paper cites.
W. Wu, Z. Qi, and L. Fuxin, “PointConv: Deep Convolutional Networks on 3D Point Clouds,” in IEEE Conf. on Computer Vision and Pattern Recognition , 2019, pp. 9621–9630
2019
Earlier work this paper cites.
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Kopf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, and S. Chintala, “Pytorch: An imperative style, high-performance deep learning library,” in Advances in Neural Information Processing Systems 32 . Curran Associates, Inc., 2019, pp. 8024–8035. [Online]. Available: http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf
2019
Earlier work this paper cites.
Y. Zhou, C. Barnes, J. Lu, J. Yang, and H. Li, “On the continuity of rotation representations in neural networks,” in IEEE Conf. on Computer Vision and Pattern Recognition , 2019, pp. 5738–5746
2019
Earlier work this paper cites.
B. Kim and L. Shimanuki, “Learning value functions with relational state representations for guiding task-and-motion planning,” in Conference on Robot Learning . PMLR, 2020, pp. 955–968
2020
Earlier work this paper cites.
2020
Cited alongside, same era.
C. R. Garrett, T. Lozano-Pérez, and L. P. Kaelbling, “Pddlstream: Integrating symbolic planners and blackbox samplers via optimistic adaptive planning,” in Proceedings of the International Conference on Automated Planning and Scheduling , vol. 30, 2020, pp. 440–448
2020
Cited alongside, same era.
2020
Cited alongside, same era.
A. Murali, A. Mousavian, C. Eppner, C. Paxton, and D. Fox, “6-dof grasping for target-driven object manipulation in clutter,” in IEEE Intl. Conf. on Robotics and Automation . IEEE, 2020, pp. 6232–6238
2020
Cited alongside, same era.
Z. Pan, A. Zeng, Y. Li, J. Yu, and K. Hauser, “Algorithms and systems for manipulating multiple objects,” IEEE Transactions on Robotics , 2022
2022
Later among the works it cites.
Y. Lin, A. S. Wang, E. Undersander, and A. Rai, “Efficient and interpretable robot manipulation with graph neural networks,” IEEE Robotics and Automation Letters , 2022
2022
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2022
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2022
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R. Li, A. Jabri, T. Darrell, and P. Agrawal, “Towards practical multi-object manipulation using relational reinforcement learning,” in IEEE Intl. Conf. on Robotics and Automation , 2020, pp. 4051–4058
2020
Cited alongside, same era.
M. Sharma and O. Kroemer, “Relational learning for skill preconditions,” in Conference on Robot Learning , 2020
2020
Cited alongside, same era.
M. Wilson and T. Hermans, “Learning to manipulate object collections using grounded state representations,” in Conference on Robot Learning , 2020, pp. 490–502
2020
Cited alongside, same era.
H. Suh and R. Tedrake, “The surprising effectiveness of linear models for visual foresight in object pile manipulation,” in Intl. Workshop on Algorithmic Foundations of Robotics , 2020
2020
Cited alongside, same era.
A. Kuntz, C. Bowen, and R. Alterovitz, “Fast Anytime Motion Planning in Point Clouds by Interleaving Sampling and Interior Point Optimization,” in International Symposium on Robotics Research (ISRR) , 2017. [Online]. Available: https://arm.cs.utah.edu/wp-content/uploads/sites/136/2020/05/Kuntz2017_ISRR.pdf
2020
Cited alongside, same era.
A. Simeonov, Y. Du, B. Kim, F. R. Hogan, J. Tenenbaum, P. Agrawal, and A. Rodriguez, “A long horizon planning framework for manipulating rigid pointcloud objects,” in Conference on Robot Learning , 2020
2020
Cited alongside, same era.
C. R. Garrett, C. Paxton, T. Lozano-Pérez, L. P. Kaelbling, and D. Fox, “Online replanning in belief space for partially observable task and motion problems,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 5678–5684
2020
Cited alongside, same era.
K. Kase, C. Paxton, H. Mazhar, T. Ogata, and D. Fox, “Transferable task execution from pixels through deep planning domain learning,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2020, pp. 10 459–10 465
2020
Cited alongside, same era.
W. Yuan, C. Paxton, K. Desingh, and D. Fox, “Sornet: Spatial object-centric representations for sequential manipulation,” in Conference on Robot Learning . PMLR, 2022, pp. 148–157
2022
Later among the works it cites.
X. Lou, Y. Yang, and C. Choi, “Learning object relations with graph neural networks for target-driven grasping in dense clutter,” in IEEE Intl. Conf. on Robotics and Automation , 2022
2022
Later among the works it cites.
D. Driess, Z. Huang, Y. Li, R. Tedrake, and M. Toussaint, “Learning multi-object dynamics with compositional neural radiance fields,” in ICRA Workshop on Motion Planning with Implicit Neural Representations of Geometry , 2022
2022
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2022
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2022
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Y. Zhu, A. Joshi, P. Stone, and Y. Zhu, “Viola: Imitation learning for vision-based manipulation with object proposal priors,” 6th Annual Conference on Robot Learning (CoRL) , 2022
2022
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2022
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2022
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T. Silver, A. Athalye, J. B. Tenenbaum, T. Lozano-Pérez, and L. P. Kaelbling, “Learning neuro-symbolic skills for bilevel planning,” in 6th Annual Conference on Robot Learning , 2022. [Online]. Available: https://openreview.net/forum?id=OIaJRUo5UXy
2022
Later among the works it cites.
K. Wada, S. James, and A. J. Davison, “ReorientBot: Learning object reorientation for specific-posed placement,” in IEEE International Conference on Robotics and Automation (ICRA) , 2022
2022
Later among the works it cites.
Y. Kim, J. Kim, and D. Park, “Graphdistnet: A graph-based collision-distance estimator for gradient-based trajectory optimization,” IEEE Robotics and Automation Letters , vol. 7, no. 4, pp. 11 118–11 125, 2022
2022
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2022
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K. Wada, S. James, and A. J. Davison, “SafePicking: Learning safe object extraction via object-level mapping,” in IEEE International Conference on Robotics and Automation (ICRA) , 2022
2022
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M. Shridhar, L. Manuelli, and D. Fox, “Perceiver-actor: A multi-task transformer for robotic manipulation,” in Proceedings of the 6th Conference on Robot Learning (CoRL) , 2022
2022
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2022
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2023
Closest in time.
B. Sundaralingam, S. K. S. Hari, A. Fishman, C. Garrett, K. Van Wyk, V. Blukis, A. Millane, H. Oleynikova, A. Handa, F. Ramos, et al. , “Curobo: Parallelized collision-free robot motion generation,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 8112–8119
2023
Closest in time.