Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 Mobile Manipulation through Deep Reinforcement Learning
Cong Wang, Qifeng Zhang, Qiyan Tian, et al.
Sensors (2020) Vol. 20, Iss. 3, pp. 939-939
Open Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

RT-1: Robotics Transformer for Real-World Control at Scale
Anthony Brohan, Noah Brown, Justice Carbajal, et al.
(2023)
Open Access | Times Cited: 154
Robot learning towards smart robotic manufacturing: A review
Zhihao Liu, Quan Liu, Wenjun Xu, et al.
Robotics and Computer-Integrated Manufacturing (2022) Vol. 77, pp. 102360-102360
Open Access | Times Cited: 121
Motion Planning for Mobile Manipulators—A Systematic Review
Thushara Sandakalum, Marcelo H. Ang
Machines (2022) Vol. 10, Iss. 2, pp. 97-97
Open Access | Times Cited: 74
Path Planning for Multi-Arm Manipulators Using Deep Reinforcement Learning: Soft Actor–Critic with Hindsight Experience Replay
Evan Prianto, MyeongSeop Kim, Jae‐Han Park, et al.
Sensors (2020) Vol. 20, Iss. 20, pp. 5911-5911
Open Access | Times Cited: 74
ReLMoGen: Integrating Motion Generation in Reinforcement Learning for Mobile Manipulation
Fei Xia, Chengshu Li, Roberto Martín-Martín, et al.
(2021), pp. 4583-4590
Closed Access | Times Cited: 55
Deep reinforcement learning based moving object grasping
Pengzhan Chen, LU Wei-qing
Information Sciences (2021) Vol. 565, pp. 62-76
Closed Access | Times Cited: 46
A systematic review on cooperative dual-arm manipulators: modeling, planning, control, and vision strategies
Mohamed Abbas, Jyotindra Narayan, Santosha K. Dwivedy
International Journal of Intelligent Robotics and Applications (2023) Vol. 7, Iss. 4, pp. 683-707
Closed Access | Times Cited: 17
ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation
Fei Xia, Chengshu Li, Roberto Martín-Martín, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 40
Methods of Condition Monitoring and Fault Detection for Electrical Machines
Karolina Kudelina, Bilal Asad, Toomas Vaimann, et al.
Energies (2021) Vol. 14, Iss. 22, pp. 7459-7459
Open Access | Times Cited: 37
Learning Kinematic Feasibility for Mobile Manipulation Through Deep Reinforcement Learning
Daniel Honerkamp, Tim Welschehold, Abhinav Valada
IEEE Robotics and Automation Letters (2021) Vol. 6, Iss. 4, pp. 6289-6296
Open Access | Times Cited: 35
A Survey of Wheeled Mobile Manipulation: A Decision-Making Perspective
Shantanu Thakar, Srivatsan Srinivasan, Sarah Al-Hussaini, et al.
Journal of Mechanisms and Robotics (2022) Vol. 15, Iss. 2
Closed Access | Times Cited: 26
A survey on deep reinforcement learning architectures, applications and emerging trends
Surjeet Balhara, Nishu Gupta, Ahmed Alkhayyat, et al.
IET Communications (2022)
Open Access | Times Cited: 24
Learning positioning policies for mobile manipulation operations with deep reinforcement learning
Ander Iriondo, Elena Lazkano, Ander Ansuategi, et al.
International Journal of Machine Learning and Cybernetics (2023) Vol. 14, Iss. 9, pp. 3003-3023
Open Access | Times Cited: 11
Advancements in Deep Reinforcement Learning and Inverse Reinforcement Learning for Robotic Manipulation: Toward Trustworthy, Interpretable, and Explainable Artificial Intelligence
Recep Özalp, Ayşegül Uçar, Cüneyt Güzelіș
IEEE Access (2024) Vol. 12, pp. 51840-51858
Open Access | Times Cited: 3
Comparison of PPO and SAC Algorithms Towards Decision Making Strategies for Collision Avoidance Among Multiple Autonomous Vehicles
Abu Jafar Md Muzahid, Syafiq Fauzi Kamarulzaman, Md. Arafatur Rahman
(2021), pp. 200-205
Closed Access | Times Cited: 20
A review of the challenges in mobile manipulation: systems design and RoboCup challenges
Martin Sereinig, Wolfgang Werth, Lisa-Marie Faller
e+i Elektrotechnik und Informationstechnik (2020) Vol. 137, Iss. 6, pp. 297-308
Open Access | Times Cited: 22
A Dynamic Multiple-Query RRT Planning Algorithm for Manipulator Obstacle Avoidance
Chengren Yuan, Changgeng Shuai, Wenqun Zhang
Applied Sciences (2023) Vol. 13, Iss. 6, pp. 3394-3394
Open Access | Times Cited: 7
Robot skill learning and the data dilemma it faces: a systematic review
Rong Jiang, Bin He, Zhipeng Wang, et al.
Robotic Intelligence and Automation (2024) Vol. 44, Iss. 2, pp. 270-286
Closed Access | Times Cited: 2
GAMMA: Graspability-Aware Mobile MAnipulation Policy Learning based on Online Grasping Pose Fusion
Jiazhao Zhang, Nandiraju Gireesh, Jilong Wang, et al.
(2024), pp. 1399-1405
Open Access | Times Cited: 2
An Easy to Use Deep Reinforcement Learning Library for AI Mobile Robots in Isaac Sim
Maximiliano Rojas, Gabriel Hermosilla, Daniel Yunge, et al.
Applied Sciences (2022) Vol. 12, Iss. 17, pp. 8429-8429
Open Access | Times Cited: 11
Learning Reward Function with Matching Network for Mapless Navigation
Qichen Zhang, Meiqiang Zhu, Liang Zou, et al.
Sensors (2020) Vol. 20, Iss. 13, pp. 3664-3664
Open Access | Times Cited: 17
Deep reinforcement learning based multi-layered traffic scheduling scheme in data center networks
Guihua Wu
Wireless Networks (2022) Vol. 30, Iss. 5, pp. 4133-4144
Closed Access | Times Cited: 9
Data quality evaluation for bridge structural health monitoring based on deep learning and frequency-domain information
Yang Deng, Hanwen Ju, Guoqiang Zhong, et al.
Structural Health Monitoring (2022) Vol. 22, Iss. 5, pp. 2925-2947
Closed Access | Times Cited: 9
ASC: Adaptive Skill Coordination for Robotic Mobile Manipulation
Naoki Yokoyama, Alexander Clegg, Joanne Truong, et al.
IEEE Robotics and Automation Letters (2023) Vol. 9, Iss. 1, pp. 779-786
Open Access | Times Cited: 4
Pre-grasp approaching on mobile robots: a pre-active layered approach
Lakshadeep Naik, Sinan Kalkan, Norbert Krüger
IEEE Robotics and Automation Letters (2024), pp. 1-8
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top