Affiliation:
1. Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark
2. Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany
Funder
Industry 4.0 lab facilities for Experimenting with Spatial and Electricity Consumption Data
Lighthouse Initiative KI.FABRIK Bayern by StMWi Bayern
Forschungs- und Entwicklungsprojekt
Bavarian State Ministry for Economic Affairs
Regional Development and Energy
SafeRoBAY
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering
Cited by
4 articles.
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1. Going Green with Lightweight Robots: Energy Optimal Programming of Lightweight Robots;2023 21st International Conference on Advanced Robotics (ICAR);2023-12-05
2. EcBot: Data-Driven Energy Consumption Open-Source MATLAB Library for Manipulators;2023 21st International Conference on Advanced Robotics (ICAR);2023-12-05
3. Labelling Lightweight Robot Energy Consumption: A Mechatronics-Based Benchmarking Metric Set;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01
4. Sizing up Energy Consumption in Lightweight Robots: A Comprehensive Assessment;2023 7th International Conference on Automation, Control and Robots (ICACR);2023-08-04