Artificial intelligence planners for multi-head path planning of SwarmItFIX agents
Author:
Funder
University of Genova, Italy
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
http://link.springer.com/content/pdf/10.1007/s10845-019-01479-8.pdf
Reference33 articles.
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3. Daoud, S., Chehade, H., Yalaoui, F., & Amodeo, L. (2014). Efficient metaheuristics for pick and place robotic systems optimization. Journal of Intelligent Manufacturing,25(1), 27–41. https://doi.org/10.1007/s10845-012-0668-z .
4. De Leonardo, L., Zlatanov, D., Zoppi, M., & Molfino, R. (2013). Design of the locomotion and docking system of the SwarmItFIX mobile fixture agent. Procedia Engineering,64, 1416–1425. https://doi.org/10.1016/j.proeng.2013.09.223 .
5. Driessens, K. (2004). Thesis: Relational reinforcement learning. AI Communications,18, 71–73.
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1. Decision Making for Multi-Robot Fixture Planning Using Multi-Agent Reinforcement Learning;IEEE Transactions on Automation Science and Engineering;2024
2. Reinforcement learning based path planning of multiple agents of SwarmItFIX robot for fixturing operation in sheetmetal milling process;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2022-02-16
3. Coordination and path planning of a heterogeneous multi-robot system for sheet metal drilling;Procedia Computer Science;2022
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