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Task-oriented object grasping and rearrangement are critical skills for robots to accomplish different real-world manipulation tasks.
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M. Kokic, J. A. Stork, J. A. Haustein, and D. Kragic, “Affordance Detection for Task-specific Grasping Using Deep Learning,” in IEEE/RAS Intl. Conf. on Humanoid Robots (Humanoids) , 2017, pp. 91–98
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R. Detry, J. Papon, and L. Matthies, “Task-oriented Grasping with Semantic and Geometric Scene Understanding,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) , 2017, pp. 3266–3273
2017
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A. Nguyen, D. Kanoulas, D. G. Caldwell, and N. G. Tsagarakis, “Object-based Affordances Detection with Convolutional Neural Networks and Dense Conditional Random Fields,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) , 2017, pp. 5908–5915
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C. R. Qi, H. Su, K. Mo, and L. J. Guibas, “PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation,” in Conf. on Computer Vision and Pattern Recognition (CVPR) , 2017, pp. 652–660
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P. R. Florence, L. Manuelli, and R. Tedrake, “Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation,” in Conference on Robot Learning (CoRL) , 2018, pp. 373–385
2018
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D. Rodriguez, C. Cogswell, S. Koo, and S. Behnke, “Transferring Grasping Skills to Novel Instances by Latent Space Non-rigid Registration,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2018, pp. 4229–4236
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D. Rodriguez and S. Behnke, “Transferring Category-based Functional Grasping Skills by Latent Space Non-rigid Registration,” IEEE Robotics and Automation Letters , vol. 3, no. 3, pp. 2662–2669, 2018
2018
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A. Kendall, Y. Gal, and R. Cipolla, “Multi-task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics,” in Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018, pp. 7482–7491
2018
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L. Mescheder, M. Oechsle, M. Niemeyer, S. Nowozin, and A. Geiger, “Occupancy Networks: Learning 3D Reconstruction in Function Space,” in Conf. on Computer Vision and Pattern Recognition (CVPR) , 2019, pp. 4460–4470
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J. J. Park, P. Florence, J. Straub, R. Newcombe, and S. Lovegrove, “DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation,” in Conf. on Computer Vision and Pattern Recognition (CVPR) , 2019, pp. 165–174
2019
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C.-Y. Chai, K.-F. Hsu, and S.-L. Tsao, “Multi-step Pick-and-place Tasks using Object-centric Dense Correspondences,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) , 2019, pp. 4004–4011
2019
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P. Ardón, E. Pairet, R. P. Petrick, S. Ramamoorthy, and K. S. Lohan, “Learning Grasp Affordance Reasoning Through Semantic Relations,” IEEE Robotics and Automation Letters , vol. 4, no. 4, pp. 4571–4578, 2019
2019
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L. Manuelli, W. Gao, P. Florence, and R. Tedrake, “KPAM: KeyPoint Affordances for Category-Level Robotic Manipulation,” in Intl. Symp. on Robotics Research , 2019, pp. 132–157
2019
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S. Prokudin, C. Lassner, and J. Romero, “Efficient Learning on Point Clouds with Basis Point Sets,” in Intl. Conf. on Computer Vision (ICCV) , 2019, pp. 4332–4341
2019
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Y. Zhou, J. Gao, and T. Asfour, “Learning Via-Point Movement Primitives with Inter- and Extrapolation Capabilities,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2019, pp. 4301–4308
2019
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T. Asfour, M. Wächter, L. Kaul, S. Rader, P. Weiner, S. Ottenhaus, R. Grimm, Y. Zhou, M. Grotz, and F. Paus, “ARMAR-6: A High-Performance Humanoid for Human-Robot Collaboration in Real World Scenarios,” IEEE Robotics and Automation Magazine , vol. 26, no. 4, pp. 108–121, 2019
2019
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K. Karunratanakul, J. Yang, Y. Zhang, M. J. Black, K. Muandet, and S. Tang, “Grasping Field: Learning Implicit Representations for Human Grasps,” in 2020 International Conference on 3D Vision (3DV) , 2020, pp. 333–344
2020
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R. Monica and J. Aleotti, “Point Cloud Projective Analysis for Part-Based Grasp Planning,” IEEE Robotics and Automation Letters , vol. 5, no. 3, pp. 4695–4702, 2020
2020
A. Simeonov, Y. Du, A. Tagliasacchi, J. B. Tenenbaum, A. Rodriguez, P. Agrawal, and V. Sitzmann, “Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2022, pp. 6394–6400
2022
Later among the works it cites.
W. Chen, H. Liang, Z. Chen, F. Sun, and J. Zhang, “Learning 6-DoF Task-oriented Grasp Detection via Implicit Estimation and Visual Affordance,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS) , 2022, pp. 762–769
2022
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B. Wen, W. Lian, K. Bekris, and S. Schaal, “CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2022, pp. 6401–6408
2022
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J. Gao, Z. Tao, N. Jaquier, and T. Asfour, “K-VIL: Keypoints-based Visual Imitation Learning,” IEEE Trans. on Robotics , vol. 39, no. 5, pp. 3888–3908, 2023
2023
Later among the works it cites.
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Cited alongside, same era.
K. Fang, Y. Zhu, A. Garg, A. Kurenkov, V. Mehta, L. Fei-Fei, and S. Savarese, “Learning Task-oriented Grasping for Tool Manipulation from Simulated Self-supervision,” Intl. Journal of Robotics Research , vol. 39, no. 2-3, pp. 202–216, 2020
2020
Cited alongside, same era.
S. Pfrommer, M. Halm, and M. Posa, “Contactnets: Learning Discontinuous Contact Dynamics with Smooth, Implicit Representations,” in Conference on Robot Learning (CoRL) , 2021, pp. 2279–2291
2021
Cited alongside, same era.
S. Yang, W. Zhang, R. Song, J. Cheng, and Y. Li, “Learning Multi-object Dense Descriptor for Autonomous Goal-conditioned Grasping,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 4109–4116, 2021
2021
Cited alongside, same era.
R. Xu, F.-J. Chu, C. Tang, W. Liu, and P. A. Vela, “An Affordance keypoint Detection Network for Robot Manipulation,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 2870–2877, 2021
2021
Cited alongside, same era.
Z. Jiang, Y. Zhu, M. Svetlik, K. Fang, and Y. Zhu, “Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations,” Robotics: Science and Systems (R:SS) , 2021
2021
Cited alongside, same era.
W. Gao and R. Tedrake, “KPAM-SC: Generalizable Manipulation Planning using Keypoint Affordance and Shape Completion,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2021, pp. 6527–6533
2021
Cited alongside, same era.
W. Gao and R. Tedrake, “KPAM 2.0: Feedback Control for Category-Level Robotic Manipulation,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 2962–2969, 2021
2021
Cited alongside, same era.
M. Sundermeyer, A. Mousavian, R. Triebel, and D. Fox, “Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes,” IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2021
2021
Cited alongside, same era.
Z. Huang, J. Xu, S. Dai, K. Xu, H. Zhang, H. Huang, and R. Hu, “NIFT: Neural Interaction Field and Template for Object Manipulation,” in IEEE Intl. Conf. on Robotics and Automation (ICRA) , 2023, pp. 1875–1881
2023
Later among the works it cites.
A. Simeonov, Y. Du, Y.-C. Lin, A. R. Garcia, L. P. Kaelbling, T. Lozano-Pérez, and P. Agrawal, “SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields,” in Conference on Robot Learning (CoRL) , 2023, pp. 835–846
2023
Later among the works it cites.
V. Holomjova, A. J. Starkey, B. Yun, and P. Meißner, “One-shot Learning for Task-oriented Grasping,” IEEE Robotics and Automation Letters , 2023
2023
Later among the works it cites.
D. Hadjivelichkov, S. Zwane, L. Agapito, M. P. Deisenroth, and D. Kanoulas, “One-Shot Transfer of Affordance Regions? AffCorrs!” in Conference on Robot Learning (CoRL) , 2023, pp. 550–560
2023
Later among the works it cites.
A. Rashid, S. Sharma, C. M. Kim, J. Kerr, L. Y. Chen, A. Kanazawa, and K. Goldberg, “Language Embedded Radiance Fields for Zero-shot Task-oriented Grasping,” in Conference on Robot Learning (CoRL) , 2023, pp. 178–200
2023
Later among the works it cites.
J. Kerr, C. M. Kim, K. Goldberg, A. Kanazawa, and M. Tancik, “LERF: Language Embedded Radiance Fields,” in Intl. Conf. on Computer Vision (ICCV) , 2023, pp. 19 729–19 739
2023
Later among the works it cites.
2023
Later among the works it cites.
D. Hidalgo-Carvajal, H. Chen, G. C. Bettelani, J. Jung, M. Zavaglia, L. Busse, A. Naceri, S. Leutenegger, and S. Haddadin, “Anthropomorphic Grasping with Neural Object Shape Completion,” IEEE Robotics and Automation Letters , 2023
2023
Later among the works it cites.
2023
Later among the works it cites.
A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, P. Dollár, and R. Girshick, “Segment Anything,” in Intl. Conf. on Computer Vision (ICCV) , 2023, pp. 3992–4003
2023
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2024
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