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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:

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

Showing 1-25 of 102 citing articles:

Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours
Lerrel Pinto, Abhinav Gupta
(2016), pp. 3406-3413
Open Access | Times Cited: 1098
Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning
Andy Zeng, Shuran Song, Stefan Welker, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018)
Open Access | Times Cited: 524
Interactive Perception: Leveraging Action in Perception and Perception in Action
Jeannette Bohg, Karol Hausman, Bharath Sankaran, et al.
IEEE Transactions on Robotics (2017) Vol. 33, Iss. 6, pp. 1273-1291
Open Access | Times Cited: 266
Deep learning a grasp function for grasping under gripper pose uncertainty
Edward Johns, Stefan Leutenegger, Andrew J. Davison
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2016), pp. 4461-4468
Open Access | Times Cited: 231
A state-of-the-art review on mobile robotics tasks using artificial intelligence and visual data
Sergio Cebollada, Luis Payá, María Flores, et al.
Expert Systems with Applications (2020) Vol. 167, pp. 114195-114195
Open Access | Times Cited: 114
A Deep Learning Approach to Grasping the Invisible
Yang Yang, Hengyue Liang, Changhyun Choi
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 2, pp. 2232-2239
Open Access | Times Cited: 89
Learning-based robotic grasping: A review
Zhen Xie, Xinquan Liang, Canale Roberto
Frontiers in Robotics and AI (2023) Vol. 10
Open Access | Times Cited: 27
Learning to Singulate Objects Using a Push Proposal Network
Andreas Eitel, Nico Hauff, Wolfram Burgard
Springer proceedings in advanced robotics (2019), pp. 405-419
Closed Access | Times Cited: 72
Linear Push Policies to Increase Grasp Access for Robot Bin Picking
Michael Danielczuk, Jeffrey Mahler, Chris Correa, et al.
2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (2018), pp. 1249-1256
Closed Access | Times Cited: 59
Efficient Learning of Goal-Oriented Push-Grasping Synergy in Clutter
Kechun Xu, Hongxiang Yu, Qianen Lai, et al.
IEEE Robotics and Automation Letters (2021) Vol. 6, Iss. 4, pp. 6337-6344
Open Access | Times Cited: 54
DIPN: Deep Interaction Prediction Network with Application to Clutter Removal
Baichuan Huang, Shuai D. Han, Abdeslam Boularias, et al.
(2021), pp. 4694-4701
Open Access | Times Cited: 49
Robotics Dexterous Grasping: The Methods Based on Point Cloud and Deep Learning
Haonan Duan, Peng Wang, Ya-Yu Huang, et al.
Frontiers in Neurorobotics (2021) Vol. 15
Open Access | Times Cited: 43
Development of robotic bin picking platform with cluttered objects using human guidance and convolutional neural network (CNN)
Jin-Ho Park, Martin Byung‐Guk Jun, Huitaek Yun
Journal of Manufacturing Systems (2022) Vol. 63, pp. 539-549
Closed Access | Times Cited: 28
Towards Robust Product Packing with a Minimalistic End-Effector
Rahul Shome, Wei Tang, Chang‐Kyu Song, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 9007-9013
Closed Access | Times Cited: 43
Robotic grasping: from wrench space heuristics to deep learning policies
J. P. Carvalho, Luís F. Rocha, P. B. de Moura Oliveira, et al.
Robotics and Computer-Integrated Manufacturing (2021) Vol. 71, pp. 102176-102176
Open Access | Times Cited: 35
Elevating Mobile Robotics: Pioneering Applications of Artificial Intelligence and Machine Learning
Haider Sahib Nasrallah, Ivan V. Stepanyan, Karrar Sahib Nassrullah, et al.
Revue d intelligence artificielle (2024) Vol. 38, Iss. 1, pp. 351-363
Open Access | Times Cited: 5
Robust object grasping in clutter via singulation
Marios Kiatos, Sotiris Malassiotis
2022 International Conference on Robotics and Automation (ICRA) (2019)
Closed Access | Times Cited: 39
Split Deep Q-Learning for Robust Object Singulation
Iason Sarantopoulos, Marios Kiatos, Zoe Doulgeri, et al.
(2020), pp. 6225-6231
Open Access | Times Cited: 35
Prehensile and Non-Prehensile Robotic Pick-and-Place of Objects in Clutter Using Deep Reinforcement Learning
Muhammad Babar Imtiaz, Yuansong Qiao, Brian Lee
Sensors (2023) Vol. 23, Iss. 3, pp. 1513-1513
Open Access | Times Cited: 11
Deep Learning a Grasp Function for Grasping under Gripper Pose Uncertainty
Edward Johns, Stefan Leutenegger, Andrew J. Davison
arXiv (Cornell University) (2016)
Closed Access | Times Cited: 34
Real-time Grasp Pose Estimation for Novel Objects in Densely Cluttered Environment
Mohit Vohra, Ravi Prakash, Laxmidhar Behera
(2019)
Open Access | Times Cited: 34
Learning Collaborative Pushing and Grasping Policies in Dense Clutter
Bingjie Tang, Matthew Corsaro, George Konidaris, et al.
(2021), pp. 6177-6184
Closed Access | Times Cited: 23
Visuo-Tactile Feedback-Based Robot Manipulation for Object Packing
Wenyu Liang, Fen Fang, Cihan Acar, et al.
IEEE Robotics and Automation Letters (2023) Vol. 8, Iss. 2, pp. 1151-1158
Closed Access | Times Cited: 10
Total Singulation With Modular Reinforcement Learning
Iason Sarantopoulos, Marios Kiatos, Zoe Doulgeri, et al.
IEEE Robotics and Automation Letters (2021) Vol. 6, Iss. 2, pp. 4117-4124
Open Access | Times Cited: 20
A Graph-Based Deep Reinforcement Learning Approach to Grasping Fully Occluded Objects
Guoyu Zuo, Jiayuan Tong, Zihao Wang, et al.
Cognitive Computation (2022) Vol. 15, Iss. 1, pp. 36-49
Closed Access | Times Cited: 15
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