Optimization of potential field method parameters through networks for swarm cooperative manipulation tasks:

International Journal of Advanced Robotic Systems

RoccoFurferi¹ 

关键词: Underwater robotics;    underwater manipulation;    autonomous underwater vehicle;    potential field method;    artificial neural networks;   

DOI  :  10.1177/1729881416657931

学科分类：自动化工程

来源: InTech

【 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.

【 授权许可】

CC BY