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Energy-Efficient Robot Configuration for Assembly
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-8906-630X
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
2017 (English)In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 139, no 5, article id 051007Article in journal (Refereed) Published
Abstract [en]

Optimizing the energy consumption of robot movements has been one of the main focuses for most of today's robotic simulation software. This optimization is based on minimizing a robot's joint movements. In many cases, it does not take into consideration the dynamic features. Therefore, reducing energy consumption is still a challenging task and it involves studying the robot's kinematic and dynamic models together with application requirements. This research aims to minimize the robot energy consumption during assembly. Given a trajectory and based on the inverse kinematics and dynamics of a robot, a set of attainable configurations for the robot can be determined, perused by calculating the suitable forces and torques on the joints and links of the robot. The energy consumption is then calculated for each configuration and based on the assigned trajectory. The ones with the lowest energy consumption are selected. Given that the energy-efficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be embedded in energy-efficient robotic assembly.

Place, publisher, year, edition, pages
The American Society of Mechanical Engineers , 2017. Vol. 139, no 5, article id 051007
Keywords [en]
industrial robots, machine-tools, consumption, optimization, constraints
National Category
Robotics
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
URN: urn:nbn:se:his:diva-13555DOI: 10.1115/1.4034935ISI: 000399395000009Scopus ID: 2-s2.0-84995900489OAI: oai:DiVA.org:his-13555DiVA, id: diva2:1094986
Available from: 2017-05-11 Created: 2017-05-11 Last updated: 2019-11-25Bibliographically approved

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Schmidt, Bernard

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  • Other locale
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