Corrigendum to “Learning-based adaption of robotic friction models” [Robotics and Computer-Integrated Manufacturing Volume 89, October 2024]

IF 11.4 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Robotics and Computer-integrated Manufacturing Pub Date : 2024-10-01 Epub Date: 2024-05-18 DOI:10.1016/j.rcim.2024.102783
Philipp Scholl , Maged Iskandar , Sebastian Wolf , Jinoh Lee , Aras Bacho , Alexander Dietrich , Alin Albu-Schäffer , Gitta Kutyniok
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基于学习的机器人摩擦模型适应"[《机器人学与计算机集成制造》第 89 卷,2024 年 10 月] 更正
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来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
期刊最新文献
State-of-the-art in mobile robot-assisted grinding technologies for large-scale complex components Physics-informed adaptive Kalman filter for contact force estimation in industrial robots considering model uncertainty Adaptive Physics-informed Transformer with Gaussian process residual compensation for inverse dynamics modeling in Human–Robot Collaboration M2OSS: A systematic research perspective on robotic machining errors An efficient occlusion-aware visibility assurance method for multi-robot vision-integrated manufacturing
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