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Automated Path Planning for Plug Produce in a Cutting-tool Changing Application
University West, Department of Engineering Science, Division of Production Systems.
University West, Department of Engineering Science, Division of Production Systems.
University West, Department of Engineering Science, Division of Production Systems.
University West, Department of Engineering Science, Division of Production Systems.ORCID iD: 0000-0002-6604-6904
2019 (English)In: 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2019, p. 356-362Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a path planning algorithm is designed and tested with a real robot for a Plug & Produce demonstrator. The demonstrator is divided into modules that can be connected and removed. Modules are used for various processes like tool change and storage. This paper focuses on the process of cutting-tool change for the production industry. The Plug & Produce demonstrator uses a multi-agent system where parts and resources are agents. A part agent, e.g., a cutting-tool, can request a robot to perform skills like transportation. This requires the robot to be autonomous. The aim of this paper is to automate the path planning for industrial robotics in a Plug & Produce system. This is done by implementing a sampling based RRT algorithm combined with a collision detection function in RobotStudio. With various real time scenarios, the path planning execution time is observed and presented in the paper.

Place, publisher, year, edition, pages
2019. p. 356-362
Keywords [en]
Collision avoidance, Industry4.0, Multi-agent systems, Path planning, Plug & Produce, Plugs, rapidly-exploring random tree, Robot kinematics, Service robots, Tools
National Category
Robotics Control Engineering Production Engineering, Human Work Science and Ergonomics
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
URN: urn:nbn:se:hv:diva-14681DOI: 10.1109/ETFA.2019.8869398Scopus ID: 2-s2.0-85074208961OAI: oai:DiVA.org:hv-14681DiVA, id: diva2:1367583
Conference
24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Available from: 2019-11-04 Created: 2019-11-04 Last updated: 2019-11-13

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Ramasamy, SudhaZhang, XiaoxiaoBennulf, MattiasDanielsson, Fredrik

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