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This paper introduces DGBench, a fully reproducible open-source testing system to enable benchmarking of dynamic grasping in environments with unpredictable relative motion between robot and object.
P. Allen, A. Timcenko, B. Yoshimi, and P. Michelman, “Automated tracking and grasping of a moving object with a robotic hand-eye system,” IEEE Transactions on Robotics and Automation , vol. 9, no. 2, pp. 152–165, 1993
1993
Earlier work this paper cites.
K. Shimoga, “Robot grasp synthesis algorithms: A survey,” The International Journal of Robotics Research , vol. 15, no. 3, pp. 230–266, 1996
1996
Earlier work this paper cites.
S. Hutchinson, G. Hager, and P. Corke, “A tutorial on visual servo control,” IEEE Transactions on Robotics and Automation , vol. 12, no. 5, pp. 651–670, 1996
1996
Earlier work this paper cites.
I. Kamon, T. Flash, and S. Edelman, “Learning to grasp using visual information,” in Proceedings of IEEE International Conference on Robotics and Automation , vol. 3, 1996, pp. 2470–2476 vol.3
1996
Earlier work this paper cites.
A. Bicchi and V. Kumar, “Robotic grasping and contact: a review,” in Proceedings IEEE International Conference on Robotics and Automation. , vol. 1, 2000, pp. 348–353
2000
Earlier work this paper cites.
A. Saxena, J. Driemeyer, and A. Y. Ng, “Robotic grasping of novel objects using vision,” The International Journal of Robotics Research , vol. 27, no. 2, pp. 157–173, 2008
2008
Earlier work this paper cites.
A. Sahbani, S. El-Khoury, and P. Bidaud, “An overview of 3d object grasp synthesis algorithms,” Robotics and Autonomous Systems , vol. 60, no. 3, pp. 326–336, 2012
2012
Earlier work this paper cites.
C. Lin, Y.-L. Chen, W. Hao, and X. Wu, “Occluded object grasping based on robot stereo vision,” in Proceedings of the 10th World Congress on Intelligent Control and Automation , 2012, pp. 3698–3704
2012
Earlier work this paper cites.
J. Bohg, A. Morales, T. Asfour, and D. Kragic, “Data-driven grasp synthesis—a survey,” IEEE Transactions on Robotics , vol. 30, no. 2, pp. 289–309, 2014
2014
Earlier work this paper cites.
B. Calli, A. Walsman, A. Singh, S. Srinivasa, P. Abbeel, and A. M. Dollar, “Benchmarking in manipulation research: Using the yale-cmu-berkeley object and model set,” IEEE Robotics Automation Magazine , vol. 22, no. 3, pp. 36–52, 2015
2015
Earlier work this paper cites.
G. Kahn, P. Sujan, S. Patil, S. Bopardikar, J. Ryde, K. Goldberg, and P. Abbeel, “Active exploration using trajectory optimization for robotic grasping in the presence of occlusions,” in IEEE International Conference on Robotics and Automation , 2015, pp. 4783–4790
2015
Earlier work this paper cites.
L. Pinto and A. Gupta, “Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours,” IEEE International Conference on Robotics and Automation , pp. 3406–3413, 2016
2016
Earlier work this paper cites.
E. Johns, S. Leutenegger, and A. J. Davison, “Deep learning a grasp function for grasping under gripper pose uncertainty,” in IEEE/RSJ International Conference on Intelligent Robots and Systems , 2016, pp. 4461–4468
2016
Cited alongside, same era.
U. Viereck, A. T. Pas, K. Saenko, and R. W. Platt, “Learning a visuomotor controller for real world robotic grasping using simulated depth images,” in Conference on Robotic Learning , 2017, pp. 291–300
2017
Cited alongside, same era.
F. Bonsignorio, “A new kind of article for reproducible research in intelligent robotics [from the field],” IEEE Robotics Automation Magazine , vol. 24, no. 3, pp. 178–182, 2017
2017
Cited alongside, same era.
Y. Chebotar, K. Hausman, O. Kroemer, G. S. Sukhatme, and S. Schaal, “Generalizing regrasping with supervised policy learning,” in 2016 International Symposium on Experimental Robotics , D. Kulić, Y. Nakamura, O. Khatib, and G. Venture, Eds. Cham: Springer International Publishing, 2017, pp. 622–632
2017
L. Berscheid, P. Meißner, and T. Kröger, “Robot learning of shifting objects for grasping in cluttered environments,” in IEEE/RSJ International Conference on Intelligent Robots and Systems , 2019
2019
Later among the works it cites.
D. Morrison, P. Corke, and J. Leitner, “Learning robust, real-time, reactive robotic grasping,” The International Journal of Robotics Research , vol. 39, no. 2-3, pp. 183–201, 2020
2020
Later among the works it cites.
S. Song, A. Zeng, J. Lee, and T. Funkhouser, “Grasping in the wild: Learning 6dof closed-loop grasping from low-cost demonstrations,” Robotics and Automation Letters , 2020
2020
Later among the works it cites.
K. Kleeberger, R. Bormann, W. Kraus, and M. Huber, “A survey on learning-based robotic grasping,” Current Robotics Reports , vol. 1, p. 239–249, 12 2020
2020
Later among the works it cites.
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Cited alongside, same era.
J. Mahler, R. Platt, A. Rodriguez, M. Ciocarlie, A. Dollar, R. Detry, M. A. Roa, H. Yanco, A. Norton, J. Falco, K. v. Wyk, E. Messina, J. Leitner, D. Morrison, M. Mason, O. Brock, L. Odhner, A. Kurenkov, M. Matl, and K. Goldberg, “Guest editorial open discussion of robot grasping benchmarks, protocols, and metrics,” IEEE Transactions on Automation Science and Engineering , vol. 15, no. 4, pp. 1440–1442, 2018
2018
Cited alongside, same era.
D. Kalashnikov, A. Irpan, P. Pastor, J. Ibarz, A. Herzog, E. Jang, D. Quillen, E. Holly, M. Kalakrishnan, V. Vanhoucke, and S. Levine, “Scalable deep reinforcement learning for vision-based robotic manipulation,” in Conference on Robot Learning , 2018
2018
Cited alongside, same era.
R. Calandra, A. Owens, D. Jayaraman, J. Lin, W. Yuan, J. Malik, E. H. Adelson, and S. Levine, “More than a feeling: Learning to grasp and regrasp using vision and touch,” IEEE Robotics and Automation Letters , vol. 3, no. 4, p. 3300–3307, Oct 2018
2018
Cited alongside, same era.
S. Levine, P. Pastor, A. Krizhevsky, J. Ibarz, and D. Quillen, “Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection,” The International Journal of Robotics Research , vol. 37, no. 4-5, pp. 421–436, 2018
2018
Cited alongside, same era.
M. Logothetis, G. C. Karras, S. Heshmati-Alamdari, P. Vlantis, and K. J. Kyriakopoulos, “A model predictive control approach for vision-based object grasping via mobile manipulator,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2018, pp. 1–6
2018
Cited alongside, same era.
N. Marturi, M. Kopicki, A. Rastegarpanah, V. Rajasekaran, M. Adjigble, R. Stolkin, A. Leonardis, and Y. Bekiroglu, “Dynamic grasp and trajectory planning for moving objects,” Autonomous Robots , vol. 43, pp. 1241–1256, 2019
2019
Cited alongside, same era.
D. Morrison, P. Corke, and J. Leitner, “Multi-view picking: Next-best-view reaching for improved grasping in clutter,” in International Conference on Robotics and Automation , 2019, pp. 8762–8768
2019
Cited alongside, same era.
A. Mousavian, C. Eppner, and D. Fox, “6-dof graspnet: Variational grasp generation for object manipulation,” IEEE/CVF International Conference on Computer Vision , pp. 2901–2910, 2019
2019
Cited alongside, same era.
Y. Yu, Z. Cao, S. Liang, W. Geng, and J. Yu, “A novel vision-based grasping method under occlusion for manipulating robotic system,” IEEE Sensors Journal , vol. 20, no. 18, pp. 10 996–11 006, 2020
2020
Later among the works it cites.
A. Zeng, S. Song, J. Lee, A. Rodriguez, and T. Funkhouser, “Tossingbot: Learning to throw arbitrary objects with residual physics,” IEEE Transactions on Robotics , vol. 36, no. 4, pp. 1307–1319, 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
P. Arora and C. Papachristos, “Mobile manipulator robot visual servoing and guidance for dynamic target grasping,” in Advances in Visual Computing , G. Bebis, Z. Yin, E. Kim, J. Bender, K. Subr, B. C. Kwon, J. Zhao, D. Kalkofen, and G. Baciu, Eds. Cham: Springer International Publishing, 2020, pp. 223–235
2020
Later among the works it cites.
I. Akinola, J. Xu, S. Song, and P. K. Allen, “Dynamic grasping with reachability and motion awareness,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2021, pp. 9422–9429
2021
Later among the works it cites.
M. Tuscher, J. Hörz, D. Driess, and M. Toussaint, “Deep 6-dof tracking of unknown objects for reactive grasping,” in 2021 IEEE International Conference on Robotics and Automation . IEEE, 2021, pp. 14 185–14 191
2021
Later among the works it cites.
C. de Farias, N. Marturi, R. Stolkin, and Y. Bekiroglu, “Simultaneous tactile exploration and grasp refinement for unknown objects,” IEEE Robotics and Automation Letters , vol. 6, no. 2, p. 3349–3356, Apr 2021
2021
Later among the works it cites.
S. Zimmermann, R. Poranne, and S. Coros, “Go fetch!-dynamic grasps using Boston Dynamics Spot with external robotic arm,” in 2021 IEEE International Conference on Robotics and Automation . IEEE, 2021, pp. 4488–4494
2021
Later among the works it cites.