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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:

Data-Driven Grasp Synthesis—A Survey
Jeannette Bohg, Antonio Morales, Tamim Asfour, et al.
IEEE Transactions on Robotics (2014) Vol. 30, Iss. 2, pp. 289-309
Open Access | Times Cited: 590

Showing 26-50 of 590 citing articles:

Intelligent In‐Vehicle Interaction Technologies
Prajval Kumar Murali, Mohsen Kaboli, Ravinder Dahiya
Advanced Intelligent Systems (2021) Vol. 4, Iss. 2
Open Access | Times Cited: 113
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: 44
Learning Object Grasping for Soft Robot Hands
Changhyun Choi, Wilko Schwarting, Joseph DelPreto, et al.
IEEE Robotics and Automation Letters (2018) Vol. 3, Iss. 3, pp. 2370-2377
Open Access | Times Cited: 158
More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch
Roberto Calandra, Andrew Owens, Dinesh Jayaraman, et al.
IEEE Robotics and Automation Letters (2018) Vol. 3, Iss. 4, pp. 3300-3307
Open Access | Times Cited: 157
Affordances in Psychology, Neuroscience, and Robotics: A Survey
Lorenzo Jamone, Emre Uğur, Angelo Cangelosi, et al.
IEEE Transactions on Cognitive and Developmental Systems (2016) Vol. 10, Iss. 1, pp. 4-25
Open Access | Times Cited: 153
Object-based affordances detection with Convolutional Neural Networks and dense Conditional Random Fields
Anh‐Tu Nguyen, Dimitrios Kanoulas, Darwin G. Caldwell, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2017), pp. 5908-5915
Closed Access | Times Cited: 149
Robot grasp detection using multimodal deep convolutional neural networks
Zhichao Wang, Zhiqi Li, Bin Wang, et al.
Advances in Mechanical Engineering (2016) Vol. 8, Iss. 9
Open Access | Times Cited: 144
PiGraphs
Manolis Savva, Anne Lynn S. Chang, Pat Hanrahan, et al.
ACM Transactions on Graphics (2016) Vol. 35, Iss. 4, pp. 1-12
Open Access | Times Cited: 132
RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real
Kanishka Rao, C.J. Harris, Alex Irpan, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 11154-11163
Open Access | Times Cited: 130
The Curious Robot: Learning Visual Representations via Physical Interactions
Lerrel Pinto, Dhiraj Gandhi, Yuanfeng Han, et al.
Lecture notes in computer science (2016), pp. 3-18
Open Access | Times Cited: 126
Shape2Pose
Vladimir G. Kim, Siddhartha Chaudhuri, Leonidas Guibas, et al.
ACM Transactions on Graphics (2014) Vol. 33, Iss. 4, pp. 1-12
Closed Access | Times Cited: 124
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
Generating multi-fingered robotic grasps via deep learning
Jacob Varley, Jonathan Weisz, J Weiss, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2015), pp. 4415-4420
Closed Access | Times Cited: 115
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
Roberto Calandra, Andrew Owens, Manu Upadhyaya, et al.
arXiv (Cornell University) (2017)
Open Access | Times Cited: 112
Towards learning hierarchical skills for multi-phase manipulation tasks
Oliver Kroemer, Christian Daniel, Gerhard Neumann, et al.
(2015)
Open Access | Times Cited: 111
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
Learning to push by grasping: Using multiple tasks for effective learning
Lerrel Pinto, Abhinav Gupta
(2017), pp. 2161-2168
Open Access | Times Cited: 107
Grasp and dexterous manipulation of multi-fingered robotic hands: a review from a control view point
Ryuta Ozawa, Kenji Tahara
Advanced Robotics (2017) Vol. 31, Iss. 19-20, pp. 1030-1050
Closed Access | Times Cited: 105
Stabilizing novel objects by learning to predict tactile slip
Filipe Veiga, Herke van Hoof, Jan Peters, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2015), pp. 5065-5072
Closed Access | Times Cited: 103
Learning to Manipulate Unknown Objects in Clutter by Reinforcement
Abdeslam Boularias, J. Andrew Bagnell, Anthony Stentz
Proceedings of the AAAI Conference on Artificial Intelligence (2015) Vol. 29, Iss. 1
Open Access | Times Cited: 102
MuJoCo HAPTIX: A virtual reality system for hand manipulation
Vikash Kumar, Emanuel Todorov
(2015), pp. 657-663
Closed Access | Times Cited: 101
Object Detection Approach for Robot Grasp Detection
Hakan Karaoğuz, Patric Jensfelt
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 4953-4959
Closed Access | Times Cited: 101
SceneGrok
Manolis Savva, Anne Lynn S. Chang, Pat Hanrahan, et al.
ACM Transactions on Graphics (2014) Vol. 33, Iss. 6, pp. 1-10
Closed Access | Times Cited: 99
Hierarchical Fingertip Space: A Unified Framework for Grasp Planning and In-Hand Grasp Adaptation
Kaiyu Hang, Miao Li, Johannes A. Stork, et al.
IEEE Transactions on Robotics (2016) Vol. 32, Iss. 4, pp. 960-972
Open Access | Times Cited: 98
Dexterous grasping under shape uncertainty
Miao Li, Kaiyu Hang, Danica Kragić, et al.
Robotics and Autonomous Systems (2015) Vol. 75, pp. 352-364
Open Access | Times Cited: 97

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