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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach
Douglas Morrison, Jürgen Leitner, Peter Corke
(2018)
Open Access | Times Cited: 490

Showing 1-25 of 490 citing articles:

Learning the signatures of the human grasp using a scalable tactile glove
Subramanian Sundaram, Petr Kellnhofer, Yunzhu Li, et al.
Nature (2019) Vol. 569, Iss. 7758, pp. 698-702
Closed Access | Times Cited: 891
Learning ambidextrous robot grasping policies
Jeffrey Mahler, Matthew Matl, Vishal Satish, et al.
Science Robotics (2019) Vol. 4, Iss. 26
Closed Access | Times Cited: 487
How to train your robot with deep reinforcement learning: lessons we have learned
Julian Ibarz, Jie Tan, Chelsea Finn, et al.
The International Journal of Robotics Research (2021) Vol. 40, Iss. 4-5, pp. 698-721
Open Access | Times Cited: 380
Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review
Guoguang Du, Kai Wang, Shiguo Lian, et al.
Artificial Intelligence Review (2020) Vol. 54, Iss. 3, pp. 1677-1734
Open Access | Times Cited: 351
Learning robust, real-time, reactive robotic grasping
Douglas Morrison, Peter Corke, Jürgen Leitner
The International Journal of Robotics Research (2019) Vol. 39, Iss. 2-3, pp. 183-201
Open Access | Times Cited: 335
GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping
Hao-Shu Fang, Chenxi Wang, Minghao Gou, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 11441-11450
Closed Access | Times Cited: 332
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pástor, et al.
Conference on Robot Learning (2018), pp. 651-673
Closed Access | Times Cited: 216
Smart Industrial Robot Control Trends, Challenges and Opportunities within Manufacturing
Jānis Ārents, Modris Greitāns
Applied Sciences (2022) Vol. 12, Iss. 2, pp. 937-937
Open Access | Times Cited: 161
Grasping in the Wild: Learning 6DoF Closed-Loop Grasping From Low-Cost Demonstrations
Shuran Song, Andy Zeng, Johnny Lee, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 3, pp. 4978-4985
Open Access | Times Cited: 140
Deep Learning Approaches to Grasp Synthesis: A Review
R. Newbury, Morris Gu, Lachlan Chumbley, et al.
IEEE Transactions on Robotics (2023) Vol. 39, Iss. 5, pp. 3994-4015
Open Access | Times Cited: 91
Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview
Zhaoxin Fan, Yazhi Zhu, Yulin He, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 4, pp. 1-40
Open Access | Times Cited: 72
Hybrid Robotic Grasping With a Soft Multimodal Gripper and a Deep Multistage Learning Scheme
Fukang Liu, Fuchun Sun, Bin Fang, et al.
IEEE Transactions on Robotics (2023) Vol. 39, Iss. 3, pp. 2379-2399
Open Access | Times Cited: 43
On-Policy Dataset Synthesis for Learning Robot Grasping Policies Using Fully Convolutional Deep Networks
Vishal Satish, Jeffrey Mahler, Ken Goldberg
IEEE Robotics and Automation Letters (2019) Vol. 4, Iss. 2, pp. 1357-1364
Closed Access | Times Cited: 122
PointNet++ Grasping: Learning An End-to-end Spatial Grasp Generation Algorithm from Sparse Point Clouds
Peiyuan Ni, Wenguang Zhang, Xiaoxiao Zhu, et al.
(2020), pp. 3619-3625
Open Access | Times Cited: 108
Deep Learning in Robotics: Survey on Model Structures and Training Strategies
Artúr I. Károly, Péter Galambos, József Kuti, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2020) Vol. 51, Iss. 1, pp. 266-279
Open Access | Times Cited: 106
On the choice of grasp type and location when handing over an object
Francesca Cini, Valerio Ortenzi, Peter Corke, et al.
Science Robotics (2019) Vol. 4, Iss. 27
Open Access | Times Cited: 94
ContactOpt: Optimizing Contact to Improve Grasps
Patrick Grady, Chengcheng Tang, Christopher D. Twigg, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
Open Access | Times Cited: 94
EGAD! An Evolved Grasping Analysis Dataset for Diversity and Reproducibility in Robotic Manipulation
Douglas Morrison, Peter Corke, Jürgen Leitner
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 3, pp. 4368-4375
Open Access | Times Cited: 89
Object-Independent Human-to-Robot Handovers Using Real Time Robotic Vision
Patrick Rosenberger, Akansel Cosgun, R. Newbury, et al.
IEEE Robotics and Automation Letters (2020) Vol. 6, Iss. 1, pp. 17-23
Open Access | Times Cited: 84
End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB
Stefan Ainetter, Friedrich Fraundorfer
(2021), pp. 13452-13458
Open Access | Times Cited: 84
RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Images
Minghao Gou, Hao-Shu Fang, Zhanda Zhu, et al.
(2021), pp. 13459-13466
Open Access | Times Cited: 83
Review of Deep Reinforcement Learning-Based Object Grasping: Techniques, Open Challenges, and Recommendations
Marwan Qaid Mohammed, Lee Chung Kwek, Shing Chyi Chua
IEEE Access (2020) Vol. 8, pp. 178450-178481
Open Access | Times Cited: 81
Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, et al.
(2021)
Open Access | Times Cited: 80
Semantics for Robotic Mapping, Perception and Interaction: A Survey
Sourav Garg, Niko Sünderhauf, Feras Dayoub, et al.
Foundations and Trends in Robotics (2020) Vol. 8, Iss. 1–2, pp. 1-224
Open Access | Times Cited: 79
Camera-to-Robot Pose Estimation from a Single Image
Timothy E. Lee, Jonathan Tremblay, Thang To, et al.
(2020)
Open Access | Times Cited: 74
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