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  • 标题:Optimization of potential field method parameters through networks for swarm cooperative manipulation tasks
  • 本地全文:下载
  • 作者:Rocco Furferi ; Roberto Conti ; Enrico Meli
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2016
  • 卷号:13
  • 期号:6
  • DOI:10.1177/1729881416657931
  • 出版社:SAGE Publications
  • 摘要:An interesting current research field related to autonomous robots is mobile manipulation performed by cooperating robots (in terrestrial, aerial and underwater environments). Focusing on the underwater scenario, cooperative manipulation of Intervention-Autonomous Underwater Vehicles (I-AUVs) is a complex and difficult application compared with the terrestrial or aerial ones because of many technical issues, such as underwater localization and limited communication. A decentralized approach for cooperative mobile manipulation of I-AUVs based on Artificial Neural Networks (ANNs) is proposed in this article. This strategy exploits the potential field method; a multi-layer control structure is developed to manage the coordination of the swarm, the guidance and navigation of I-AUVs and the manipulation task. In the article, this new strategy has been implemented in the simulation environment, simulating the transportation of an object. This object is moved along a desired trajectory in an unknown environment and it is transported by four underwater mobile robots, each one provided with a seven-degrees-of-freedom robotic arm. The simulation results are optimized thanks to the ANNs used for the potentials tuning.
  • 关键词:Underwater robotics ; underwater manipulation ; autonomous underwater vehicle ; potential field method ; artificial neural networks
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