The multi -criteria effectiveness evaluation of the robotic group based on 3D real-time vision system

Mikhail V. Ivanov, O. Sergiyenko, L. Lindner, Paolo Mercorelli, Julio Cesar Rodrjguez-Quiñonez, W. Flores-Fuentes
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引用次数: 2

Abstract

Robotic group collaboration in a densely cluttered terrain is one of the main problems in mobile robotics control. This article describes the basic set of tasks solved to model a robotic group behavior during the distributed search of an object (goal) with parallel mapping. The navigation scheme uses the benefits of the authors' original technical vision system (TVS) based on dynamic triangulation principles. According to the TVS output data, fuzzy logic rules of resolution stabilization were implemented; with the aim to improve the data exchange. Modified dynamic communication network model and implemented the propagation of information with a feedback method to improve the data exchange inside the robotic group. For forming the continuous and energy-saving trajectory authors are proposing to use the two-steps post-processing method of path planning with polygon approximation. The combination of our collective TVS scans fusion and modified dynamic data exchange network forming method with adjustment of the known path planning methods can improve the robotic motion planning and navigation in unknown cluttered terrain. The authors presented the results of group effectiveness based on unique detected data, analysis of completion time, and entropy reduction results based on the size of a robot group.
基于三维实时视觉系统的机器人群多准则有效性评价
机器人群体在密集杂乱地形中的协作是移动机器人控制中的主要问题之一。本文描述了在并行映射的对象(目标)分布式搜索过程中建模机器人群体行为的基本任务集。该导航方案利用了作者独创的基于动态三角测量原理的技术视觉系统(TVS)的优点。根据TVS输出数据,实现了分辨率稳定的模糊逻辑规则;目的是改善数据交换。改进了动态通信网络模型,采用反馈的方式实现了信息的传播,提高了机器人群体内部的数据交换能力。为了形成连续节能的轨迹,提出了基于多边形逼近的两步路径规划后处理方法。将我们的集体TVS扫描融合和改进的动态数据交换网络形成方法与已知路径规划方法的调整相结合,可以提高机器人在未知杂乱地形中的运动规划和导航能力。作者介绍了基于唯一检测数据的群体有效性的结果,完成时间的分析,以及基于机器人群体规模的熵减少结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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