基于自组织身体模式的前馈编队控制

J. Franco-Robles, J. Escareño, D. Soto-Guerrero, O. Labbani-Igbida
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引用次数: 1

摘要

本文提出了一种新的自组织体模式(SO-BoS)系统架构,该系统能够相对于单个传感器空间学习三架旋翼机的构型空间。SO-BoS皮层图结构代表合成人体姿势的感觉-运动(圆反应)的后顶叶皮层;我们在这个过程的启发下,控制了三架旋翼无人机的编队位移。基于so - bos的前馈控制驱动空中机器人编队向目标位置移动,同时避开障碍物和智能体间碰撞。由于学习-咿呀学语阶段产生的可塑性,提出的策略是一种很有前途的方法。给出了数值结果部分,对所提出的智能导航方案的有效性进行了固有的讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feedforward Formation Control based on Self-Organized Body-Schema
In this paper we propose a new architecture of the self-organized body schema (SO-BoS) system capable of learning the configuration space of three rotorcrafts relative to a single sensor space. The SO-BoS cortical map architecture represents the posterior parietal cortex where sensory-motor of the human posture is synthesized (circular-reaction); we inspired on such process to control the displacement in formation of three rotorcraft UAVs. The SO-BoS-based feedforward control drives the aerial robots formation towards the desired position while avoiding obstacles and inter-agent collisions. The proposed strategy is a promising approach for aerial vehicles systems due to the plasticity resulting from the learning-babbling stage. A numerical result section is given to provide the inherent discussions to assess the effectiveness of the proposed intelligent navigation scheme.
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