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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:

Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human–Robot Interaction
Juan M. Gandarías, Jesús M. Gómez-de-Gabriel, Alfonso García-Cerezo
Sensors (2018) Vol. 18, Iss. 3, pp. 692-692
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

A Review of Tactile Information: Perception and Action Through Touch
Qiang Li, Oliver Kroemer, Zhe Su, et al.
IEEE Transactions on Robotics (2020) Vol. 36, Iss. 6, pp. 1619-1634
Open Access | Times Cited: 207
CNN-Based Methods for Object Recognition With High-Resolution Tactile Sensors
Juan M. Gandarías, Alfonso García-Cerezo, Jesús M. Gómez-de-Gabriel
IEEE Sensors Journal (2019) Vol. 19, Iss. 16, pp. 6872-6882
Open Access | Times Cited: 103
Modeling and analysis of soft robotic fingers using the fin ray effect
Xiaowei Shan, Lionel Birglen
The International Journal of Robotics Research (2020) Vol. 39, Iss. 14, pp. 1686-1705
Closed Access | Times Cited: 72
Human-Robot Interaction Review: Challenges and Solutions for Modern Industrial Environments
Diego Rodriguez-Guerra, Gorka Sorrosal, Itziar Cabanes, et al.
IEEE Access (2021) Vol. 9, pp. 108557-108578
Open Access | Times Cited: 68
3D Printing of Robotic Soft Grippers: Toward Smart Actuation and Sensing
Guo Dong Goh, Guo Liang Goh, Zheng Lyu, et al.
Advanced Materials Technologies (2022) Vol. 7, Iss. 11
Open Access | Times Cited: 64
Comprehensive Review on Reaching and Grasping of Objects in Robotics
Marwan Qaid Mohammed, Shing Chyi Chua, Lee Chung Kwek
Robotica (2021) Vol. 39, Iss. 10, pp. 1849-1882
Closed Access | Times Cited: 59
Recent Advances in Perceptive Intelligence for Soft Robotics
Zhuofan Lin, Ziya Wang, Wenyu Zhao, et al.
Advanced Intelligent Systems (2023) Vol. 5, Iss. 5
Open Access | Times Cited: 30
A comprehensive review of robot intelligent grasping based on tactile perception
Tong Li, Yuhang Yan, Chengshun Yu, et al.
Robotics and Computer-Integrated Manufacturing (2024) Vol. 90, pp. 102792-102792
Closed Access | Times Cited: 8
Learning Spatio Temporal Tactile Features with a ConvLSTM for the Direction Of Slip Detection
Brayan S. Zapata-Impata, Pablo Gil, Fernando Torres
Sensors (2019) Vol. 19, Iss. 3, pp. 523-523
Open Access | Times Cited: 74
Recent Progress of Biomimetic Tactile Sensing Technology Based on Magnetic Sensors
Jiandong Man, Guangyuan Chen, Jiamin Chen
Biosensors (2022) Vol. 12, Iss. 11, pp. 1054-1054
Open Access | Times Cited: 35
Bayesian and Neural Inference on LSTM-Based Object Recognition From Tactile and Kinesthetic Information
Francisco Pastor, Jorge García-González, Juan M. Gandarías, et al.
IEEE Robotics and Automation Letters (2020) Vol. 6, Iss. 1, pp. 231-238
Open Access | Times Cited: 47
A 3D-Printed Fin Ray Effect Inspired Soft Robotic Gripper with Force Feedback
Yang Yang, Kaixiang Jin, Honghui Zhu, et al.
Micromachines (2021) Vol. 12, Iss. 10, pp. 1141-1141
Open Access | Times Cited: 36
Using 3D Convolutional Neural Networks for Tactile Object Recognition with Robotic Palpation
Francisco Pastor, Juan M. Gandarías, Alfonso García-Cerezo, et al.
Sensors (2019) Vol. 19, Iss. 24, pp. 5356-5356
Open Access | Times Cited: 40
Texture Recognition Based on Perception Data from a Bionic Tactile Sensor
Shiyao Huang, Hao Wu
Sensors (2021) Vol. 21, Iss. 15, pp. 5224-5224
Open Access | Times Cited: 31
Bioinspired Tactile Object Identification Leveraging Deep Learning and Soft Body Compliance
Oliver Shorthose, Luca Scimeca, Alessandro Albini, et al.
Advanced Intelligent Systems (2025)
Open Access
Open-Loop Position Control in Collaborative, Modular Variable-Stiffness-Link (VSL) Robots
Juan M. Gandarías, Yongjing Wang, Agostino Stilli, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 2, pp. 1772-1779
Open Access | Times Cited: 29
Intrinsic Contact Sensing and Object Perception of an Adaptive Fin-Ray Gripper Integrating Compact Deflection Sensors
Genliang Chen, Shujie Tang, Shaoqiu Xu, et al.
IEEE Transactions on Robotics (2023) Vol. 39, Iss. 6, pp. 4482-4499
Closed Access | Times Cited: 9
A Deep Learning Method for Vision Based Force Prediction of a Soft Fin Ray Gripper Using Simulation Data
Daniel De Barrie, Manjari Pandya, Harit Pandya, et al.
Frontiers in Robotics and AI (2021) Vol. 8
Open Access | Times Cited: 22
Partial Visual-Tactile Fused Learning for Robotic Object Recognition
Tao Zhang, Yang Cong, Jiahua Dong, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2021) Vol. 52, Iss. 7, pp. 4349-4361
Closed Access | Times Cited: 19
A variable stiffness robotic gripper based on parallel beam with vision-based force sensing for flexible grasping
Jiaming Fu, Ziqing Yu, Qianyu Guo, et al.
Robotica (2023), pp. 1-19
Open Access | Times Cited: 7
Implementation of multiple controllers for context-inspired collaboration between human and robot by integrating the uni-axial motion and real-time operating system
Dang Quy Phan, Ha Quang Thinh Ngo
Internet of Things (2023) Vol. 22, pp. 100788-100788
Closed Access | Times Cited: 6
RGB-D Object Recognition Using Multi-Modal Deep Neural Network and DS Evidence Theory
Hui Zeng, Bin Yang, Xiuqing Wang, et al.
Sensors (2019) Vol. 19, Iss. 3, pp. 529-529
Open Access | Times Cited: 18
Pressure distribution classification and segmentation of human hands in contact with the robot body
Alessandro Albini, Giorgio Cannata
The International Journal of Robotics Research (2020) Vol. 39, Iss. 6, pp. 668-687
Open Access | Times Cited: 17
Visual–tactile object recognition of a soft gripper based on faster Region-based Convolutional Neural Network and machining learning algorithm
Chenlei Jiao, Binbin Lian, Zhe Wang, et al.
International Journal of Advanced Robotic Systems (2020) Vol. 17, Iss. 5
Open Access | Times Cited: 17
Geometric Conformity Study of a Fin Ray Gripper Utilizing Active Haptic Control
Christian Ivan Basson, Glen Bright
(2019), pp. 713-718
Closed Access | Times Cited: 15
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