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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:

Sim-to-Real Transfer for Optical Tactile Sensing
Zihan Ding, Nathan F. Lepora, Edward Johns
(2020), pp. 1639-1645
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey
Wenshuai Zhao, Jorge Peña Queralta, Tomi Westerlund
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2020), pp. 737-744
Open Access | Times Cited: 493
3D printing of resilient biogels for omnidirectional and exteroceptive soft actuators
Andreas Heiden, David Preninger, Lukas E. Lehner, et al.
Science Robotics (2022) Vol. 7, Iss. 63
Open Access | Times Cited: 109
Soft Biomimetic Optical Tactile Sensing With the TacTip: A Review
Nathan F. Lepora
IEEE Sensors Journal (2021) Vol. 21, Iss. 19, pp. 21131-21143
Open Access | Times Cited: 107
TACTO: A Fast, Flexible, and Open-Source Simulator for High-Resolution Vision-Based Tactile Sensors
Shaoxiong Wang, Mike Lambeta, Po-Wei Chou, et al.
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 2, pp. 3930-3937
Open Access | Times Cited: 87
Generation of GelSight Tactile Images for Sim2Real Learning
Daniel Fernandes Gomes, Paolo Paoletti, Shan Luo
IEEE Robotics and Automation Letters (2021) Vol. 6, Iss. 2, pp. 4177-4184
Open Access | Times Cited: 63
Taxim: An Example-Based Simulation Model for GelSight Tactile Sensors
Zilin Si, Wenzhen Yuan
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 2, pp. 2361-2368
Open Access | Times Cited: 47
Visuo-haptic object perception for robots: an overview
Nicolás Navarro-Guerrero, Sibel Toprak, Josip Josifovski, et al.
Autonomous Robots (2023) Vol. 47, Iss. 4, pp. 377-403
Open Access | Times Cited: 24
Simulation, Learning, and Application of Vision-Based Tactile Sensing at Large Scale
Quan Khanh Luu, Nhan Huu Nguyen, Van Anh Ho
IEEE Transactions on Robotics (2023) Vol. 39, Iss. 3, pp. 2003-2019
Open Access | Times Cited: 21
Sim-to-Real for Robotic Tactile Sensing via Physics-Based Simulation and Learned Latent Projections
Yashraj Narang, Balakumar Sundaralingam, Miles Macklin, et al.
(2021)
Open Access | Times Cited: 38
Bidirectional Sim-to-Real Transfer for GelSight Tactile Sensors With CycleGAN
Weihang Chen, Yuan Xu, Zhenyang Chen, et al.
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 3, pp. 6187-6194
Closed Access | Times Cited: 28
Tactile Gym 2.0: Sim-to-Real Deep Reinforcement Learning for Comparing Low-Cost High-Resolution Robot Touch
Yijiong Lin, John W. Lloyd, Alex Church, et al.
IEEE Robotics and Automation Letters (2022) Vol. 7, Iss. 4, pp. 10754-10761
Open Access | Times Cited: 25
Simulation of Vision-based Tactile Sensors using Physics based Rendering
Arpit Agarwal, Timothy Man, Wenzhen Yuan
(2021), pp. 1-7
Open Access | Times Cited: 32
Continuous Marker Patterns for Representing Contact Information in Vision-Based Tactile Sensor: Principle, Algorithm, and Verification
Mingxuan Li, Lunwei Zhang, Tiemin Li, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-12
Closed Access | Times Cited: 21
Unsupervised Adversarial Domain Adaptation for Sim-to-Real Transfer of Tactile Images
Xingshuo Jing, Kun Qian, Tudor Jianu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 12
Pushing with Soft Robotic Arms via Deep Reinforcement Learning
Carlo Alessi, Diego Bianchi, Gianni Stano, et al.
Advanced Intelligent Systems (2024) Vol. 6, Iss. 8
Open Access | Times Cited: 4
Reducing Cross-Sensor Domain Gaps in Tactile Sensing via Few-Sample-Driven Style-to-Content Unsupervised Domain Adaptation
Xingshuo Jing, Kun Qian
Sensors (2025) Vol. 25, Iss. 1, pp. 256-256
Open Access
Sim-to-Real for High-Resolution Optical Tactile Sensing: From Images to Three-Dimensional Contact Force Distributions
Carmelo Sferrazza, Raffaello D’Andrea
Soft Robotics (2021) Vol. 9, Iss. 5, pp. 926-937
Open Access | Times Cited: 25
Soft Biomimetic Optical Tactile Sensing with the TacTip: A Review
Nathan F. Lepora
(2021)
Open Access | Times Cited: 24
Crossing the Gap: A Deep Dive into Zero-Shot Sim-to-Real Transfer for Dynamics
Eugene Valassakis, Zihan Ding, Edward Johns
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2020), pp. 5372-5379
Open Access | Times Cited: 27
Zero-Shot Sim-to-Real Transfer of Tactile Control Policies for Aggressive Swing-Up Manipulation
Thomas Bi, Carmelo Sferrazza, Raffaello D’Andrea
IEEE Robotics and Automation Letters (2021) Vol. 6, Iss. 3, pp. 5761-5768
Open Access | Times Cited: 19
HiVTac: A High-Speed Vision-Based Tactile Sensor for Precise and Real-Time Force Reconstruction with Fewer Markers
Shengjiang Quan, Xiao Liang, Hairui Zhu, et al.
Sensors (2022) Vol. 22, Iss. 11, pp. 4196-4196
Open Access | Times Cited: 12
A Transferability Metric Using Scene Similarity and Local Map Observation for DRL Navigation
Shiwei Lian, Feitian Zhang
IEEE/ASME Transactions on Mechatronics (2024), pp. 1-11
Open Access | Times Cited: 2
FOTS: A Fast Optical Tactile Simulator for Sim2Real Learning of Tactile-Motor Robot Manipulation Skills
Yongqiang Zhao, Kun Qian, Boyi Duan, et al.
IEEE Robotics and Automation Letters (2024) Vol. 9, Iss. 6, pp. 5647-5654
Open Access | Times Cited: 2
Enhancing Deep Reinforcement Learning Approaches for Multi-Robot Navigation via Single-Robot Evolutionary Policy Search
Enrico Marchesini, Alessandro Farinelli
2022 International Conference on Robotics and Automation (ICRA) (2022), pp. 5525-5531
Closed Access | Times Cited: 9
Sim-to-Real Model-Based and Model-Free Deep Reinforcement Learning for Tactile Pushing
Max Yang, Yijiong Lin, Alex Church, et al.
IEEE Robotics and Automation Letters (2023) Vol. 8, Iss. 9, pp. 5480-5487
Open Access | Times Cited: 5
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