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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:

Using probabilistic movement primitives in robotics
Alexandros Paraschos, Christian Daniel, Jan Peters, et al.
Autonomous Robots (2017) Vol. 42, Iss. 3, pp. 529-551
Closed Access | Times Cited: 171

Showing 1-25 of 171 citing articles:

Kernelized movement primitives
Yanlong Huang, Leonel Rozo, João Silvério, et al.
The International Journal of Robotics Research (2019) Vol. 38, Iss. 7, pp. 833-852
Open Access | Times Cited: 188
The future of General Movement Assessment: The role of computer vision and machine learning – A scoping review
Nelson Silva, Dajie Zhang, Tomas Kulviĉius, et al.
Research in Developmental Disabilities (2021) Vol. 110, pp. 103854-103854
Open Access | Times Cited: 92
ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives
Ge Li, Zeqi Jin, Michael Volpp, et al.
IEEE Robotics and Automation Letters (2023) Vol. 8, Iss. 4, pp. 2325-2332
Closed Access | Times Cited: 22
RL-Based Adaptive Controller for High Precision Reaching in a Soft Robot Arm
Muhammad Sunny Nazeer, Cecilia Laschi, Egidio Falotico
IEEE Transactions on Robotics (2024) Vol. 40, pp. 2498-2512
Open Access | Times Cited: 8
Sampling-Based Motion Planning: A Comparative Review
Andreas Orthey, Constantinos Chamzas, Lydia E. Kavraki
Annual Review of Control Robotics and Autonomous Systems (2023) Vol. 7, Iss. 1, pp. 285-310
Open Access | Times Cited: 19
Towards autonomous selective harvesting: A review of robot perception, robot design, motion planning and control
Vishnu Rajendran, Bappaditya Debnath, Sariah Mghames, et al.
Journal of Field Robotics (2023) Vol. 41, Iss. 7, pp. 2247-2279
Open Access | Times Cited: 18
Learning and generalization of task-parameterized skills through few human demonstrations
Adrián Prados, Santiago Garrido, Ramón Barber
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108310-108310
Open Access | Times Cited: 6
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation
F. Frank, Alexandros Paraschos, Patrick van der Smagt, et al.
IEEE Transactions on Robotics (2021) Vol. 38, Iss. 4, pp. 2276-2294
Open Access | Times Cited: 35
A Human–Robot Skill Transfer Strategy with Task-Constrained Optimization and Real-Time Whole-Body Adaptation
Guanwen Ding, Xizhe Zang, Xuehe Zhang, et al.
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3171-3171
Open Access
Human Posture Prediction During Physical Human-Robot Interaction
Lorenzo Vianello, Jean-Baptiste Mouret, Eloïse Dalin, et al.
IEEE Robotics and Automation Letters (2021) Vol. 6, Iss. 3, pp. 6046-6053
Open Access | Times Cited: 29
Gaussian-process-based robot learning from demonstration
Miguel Arduengo, Adrià Colomé, Joan Lobo-Prat, et al.
Journal of Ambient Intelligence and Humanized Computing (2023)
Open Access | Times Cited: 10
Improving Local Trajectory Optimisation using Probabilistic Movement Primitives
R. B. Ashith Shyam, Peter Lightbody, Gautham P. Das, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2019), pp. 2666-2671
Open Access | Times Cited: 33
Learning Intention Aware Online Adaptation of Movement Primitives
Dorothea Koert, Joni Pajarinen, Albert Schotschneider, et al.
IEEE Robotics and Automation Letters (2019) Vol. 4, Iss. 4, pp. 3719-3726
Closed Access | Times Cited: 30
Plucking Motions for Tea Harvesting Robots Using Probabilistic Movement Primitives
Kurena Motokura, Masaki Takahashi, Marco Ewerton, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 2, pp. 3275-3282
Closed Access | Times Cited: 30
Robot recognizing humans intention and interacting with humans based on a multi-task model combining ST-GCN-LSTM model and YOLO model
Chunfang Liu, Xiaoli Li, Qing Li, et al.
Neurocomputing (2020) Vol. 430, pp. 174-184
Closed Access | Times Cited: 29
A Framework for Recognition and Prediction of Human Motions in Human-Robot Collaboration Using Probabilistic Motion Models
Thomas Callens, Arthur van der Have, Sam Van Rossom, et al.
IEEE Robotics and Automation Letters (2020) Vol. 5, Iss. 4, pp. 5151-5158
Open Access | Times Cited: 28
An adaptive framework of real-time continuous gait phase variable estimation for lower-limb wearable robots
Binquan Zhang, Sun’an Wang, Min Zhou, et al.
Robotics and Autonomous Systems (2021) Vol. 143, pp. 103842-103842
Closed Access | Times Cited: 24
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning
Michael Lutter, Johannes Silberbauer, Joe Watson, et al.
(2021)
Open Access | Times Cited: 24
A neural network based framework for variable impedance skills learning from demonstrations
Yu Zhang, Long Cheng, Ran Cao, et al.
Robotics and Autonomous Systems (2022) Vol. 160, pp. 104312-104312
Closed Access | Times Cited: 18
A novel framework to improve motion planning of robotic systems through semantic knowledge-based reasoning
Rodrigo Bernardo, João M. C. Sousa, Paulo Gonçalves
Computers & Industrial Engineering (2023) Vol. 182, pp. 109345-109345
Open Access | Times Cited: 10
Learning Skills From Demonstrations: A Trend From Motion Primitives to Experience Abstraction
Mehrdad Tavassoli, Sunny Katyara, María Pozzi, et al.
IEEE Transactions on Cognitive and Developmental Systems (2023) Vol. 16, Iss. 1, pp. 57-74
Open Access | Times Cited: 9
A trajectory planning method for robotic arms based on improved dynamic motion primitives
Xiaohui Jia, Bin Zhao, Jinyue Liu, et al.
Industrial Robot the international journal of robotics research and application (2024) Vol. 51, Iss. 5, pp. 847-856
Closed Access | Times Cited: 3
Learning from Demonstrations in Human–Robot Collaborative Scenarios: A Survey
Arturo Daniel Sosa-Ceron, Hugo G. González-Hernández, Jorge A. Reyes-Avendaño
Robotics (2022) Vol. 11, Iss. 6, pp. 126-126
Open Access | Times Cited: 14
Imitation and mirror systems in robots through Deep Modality Blending Networks
M. Yunus Seker, Alper Ahmetoğlu, Yukie Nagai, et al.
Neural Networks (2021) Vol. 146, pp. 22-35
Open Access | Times Cited: 19
K-VIL: Keypoints-Based Visual Imitation Learning
Jianfeng Gao, Zhi Tao, Noémie Jaquier, et al.
IEEE Transactions on Robotics (2023) Vol. 39, Iss. 5, pp. 3888-3908
Open Access | Times Cited: 7
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