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

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Robotics and Computer-integrated Manufacturing Pub 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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Corrigendum to “Learning-based adaption of robotic friction models” [Robotics and Computer-Integrated Manufacturing Volume 89, October 2024]
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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
Knowledge extraction for additive manufacturing process via named entity recognition with LLMs Digital Twin-driven multi-scale characterization of machining quality: current status, challenges, and future perspectives A dual knowledge embedded hybrid model based on augmented data and improved loss function for tool wear monitoring A real-time collision avoidance method for redundant dual-arm robots in an open operational environment Less gets more attention: A novel human-centered MR remote collaboration assembly method with information recommendation and visual enhancement
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