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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:

Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks
Roberto Martín-Martín, Michelle A. Lee, Rachel Gardner, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2019), pp. 1010-1017
Open Access | Times Cited: 151

Showing 26-50 of 151 citing articles:

Structured World Models from Human Videos
Russell Mendonca, Shikhar Bahl, Deepak Pathak
(2023)
Open Access | Times Cited: 11
Sensorimotor Learning With Stability Guarantees Via Autonomous Neural Dynamic Policies
Dionis Totsila, Konstantinos Chatzilygeroudis, Valerio Modugno, et al.
IEEE Robotics and Automation Letters (2025) Vol. 10, Iss. 2, pp. 1760-1767
Closed Access
Research on End-Effector Decoupling Control Strategy Based on Dual Force Sensors
Ying Zhong, Han Chen, Chin-Yin Chen, et al.
Lecture notes in computer science (2025), pp. 261-274
Closed Access
A Symmetric Stiffness Matrix Design for Robotic On-orbit Refueling Operations Control
Rui Zhang, Qiang Zhang, Xiaodong Zhou
Lecture notes in electrical engineering (2025), pp. 356-365
Closed Access
A Novel Hand Teleoperation Method with Force and Vibrotactile Feedback Based on Dynamic Compliant Primitives Controller
Peixuan Hu, Xiao Huang, Yunlai Wang, et al.
Biomimetics (2025) Vol. 10, Iss. 4, pp. 194-194
Open Access
Robust Quadruped Jumping via Deep Reinforcement Learning
Guillaume Bellegarda, Quan Nguyen
arXiv (Cornell University) (2020)
Open Access | Times Cited: 29
Learning Force Control for Contact-Rich Manipulation Tasks With Rigid Position-Controlled Robots
Cristian C. Beltran-Hernandez, Damien Petit, Ixchel G. Ramirez-Alpizar, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 4, pp. 5709-5716
Open Access | Times Cited: 28
Neural Dynamic Policies for End-to-End Sensorimotor Learning
Shikhar Bahl, Mustafa Mukadam, Abhinav Gupta, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 28
InsertionNet - A Scalable Solution for Insertion
Oren Spector, Dotan Di Castro
IEEE Robotics and Automation Letters (2021) Vol. 6, Iss. 3, pp. 5509-5516
Open Access | Times Cited: 26
Offline Reinforcement Learning of Robotic Control Using Deep Kinematics and Dynamics
Xiang Li, Weiwei Shang, Shuang Cong
IEEE/ASME Transactions on Mechatronics (2024) Vol. 29, Iss. 4, pp. 2428-2439
Closed Access | Times Cited: 3
Hybrid Trajectory and Force Learning of Complex Assembly Tasks: A Combined Learning Framework
Yan Wang, Cristian C. Beltran-Hernandez, Weiwei Wan, et al.
IEEE Access (2021) Vol. 9, pp. 60175-60186
Open Access | Times Cited: 22
Learning Dense Rewards for Contact-Rich Manipulation Tasks
Zheng Wu, Wenzhao Lian, Vaibhav Unhelkar, et al.
(2021), pp. 6214-6221
Open Access | Times Cited: 22
LASER: Learning a Latent Action Space for Efficient Reinforcement Learning
Arthur Allshire, Roberto Martín-Martín, Charles C. Lin, et al.
(2021), pp. 6650-6656
Open Access | Times Cited: 21
An Optimal Variable Impedance Control With Consideration of the Stability
Zhehao Jin, Andong Liu, Wen‐An Zhang, et al.
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 2, pp. 1737-1744
Closed Access | Times Cited: 15
Skill-based Multi-objective Reinforcement Learning of Industrial Robot Tasks with Planning and Knowledge Integration
Matthias Mayr, Faseeh Ahmad, Konstantinos Chatzilygeroudis, et al.
2021 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2022), pp. 1995-2002
Open Access | Times Cited: 15
The model reference adaptive impedance control for underwater manipulator compliant operation
Jianjun Zhang, Li Han, Qunpo Liu, et al.
Transactions of the Institute of Measurement and Control (2023) Vol. 45, Iss. 11, pp. 2135-2148
Closed Access | Times Cited: 9
Study on force control for robot massage with a model-based reinforcement learning algorithm
Meng Xiao, Tie Zhang, Yanbiao Zou, et al.
Intelligent Service Robotics (2023) Vol. 16, Iss. 4, pp. 509-519
Closed Access | Times Cited: 9
Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors
Michelle A. Lee, Matthew Tan, Yuke Zhu, et al.
(2021)
Open Access | Times Cited: 20
Force-guided autonomous robotic ultrasound scanning control method for soft uncertain environment
Guochen Ning, Jiaqi Chen, Xinran Zhang, et al.
International Journal of Computer Assisted Radiology and Surgery (2021) Vol. 16, Iss. 12, pp. 2189-2199
Closed Access | Times Cited: 19
BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
Sanjana Srivastava, Chengshu Li, Michael Lingelbach, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 19
Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation
Niklas Funk, Charles Schaff, Rishabh Madan, et al.
IEEE Robotics and Automation Letters (2021) Vol. 7, Iss. 1, pp. 478-485
Open Access | Times Cited: 19
Design and analysis of a variable-stiffness robotic gripper
Daniel Cardin-Catalan, Simon Ceppetelli, Ángel P. del Pobil, et al.
Alexandria Engineering Journal (2021) Vol. 61, Iss. 2, pp. 1235-1248
Open Access | Times Cited: 18
A Learning Based Hierarchical Control Framework for Human–Robot Collaboration
Zhehao Jin, Andong Liu, Wen‐An Zhang, et al.
IEEE Transactions on Automation Science and Engineering (2022) Vol. 20, Iss. 1, pp. 506-517
Closed Access | Times Cited: 13
Variable Impedance Skill Learning for Contact-Rich Manipulation
Quantao Yang, Alexander Dürr, Elin Anna Topp, et al.
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 3, pp. 8391-8398
Open Access | Times Cited: 13
Guided Reinforcement Learning: A Review and Evaluation for Efficient and Effective Real-World Robotics [Survey]
Julian Eßer, Nicolas Bach, Christian Jestel, et al.
IEEE Robotics & Automation Magazine (2022) Vol. 30, Iss. 2, pp. 67-85
Open Access | Times Cited: 13

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