机器人系统群控制单元的集体目标识别模型

Oleg A. Kaunov, M. Kochetkov, Vladimir F. Petrov, Aleksey I. Terent’ev
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引用次数: 0

摘要

目前的一项实际任务是在自然灾害和人为灾害地区进行大面积监测。机器人的成组使用使得可以扩大控制区域的大小,增加检测各种目的物体的概率。同时,在物体观察条件存在先验不确定性的情况下,物体识别任务也出现了新的问题。本文提出了一种新的方法来解决一群机器人综合体的集体目标识别问题,当自主机器人对主要目标进行识别,并在控制点制定最终解决方案时,考虑到制定主要识别决策的具体条件。提出了一种通用的集体目标识别模型,考虑了信息处理的各个阶段,并给出了必要的公式依赖关系。通过实例说明了该方法的特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model of Collective Object Recognition at the Control Unit of a Robot Systems Group
Nowadays an actual task is large territories monitoring in areas of natural and anthropogenic disasters. Group use of robots makes it possible to enlarge the size of the controlled zone, increase the probability of detecting objects of various purposes. At the same time, there appear new problems related to the task of objects recognition in conditions of a priori uncertainty regarding their observation conditions.The article offers a new approach to solving the problem of collective object recognition of a group robotic complexes, when the primary object recognition by autonomous robots, and the final solution is developed at the control point, taking into account the specific conditions under which decisions on primary recognition were developed.A general model of collective object recognition is presented, certain stages of information processing are considered, and the necessary formula dependencies are given. The features of the proposed approach are explained by examples.
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