Path Planning Model of Intelligent Robot based on Computer Vision Recognition Algorithm

Xiaolei Zhang, Xiaotao Zhang
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Abstract

This study has designed a path planning model for intelligent robot based on computer vision recognition algorithm. Here, the redundant nodes present in the pre-planned path are removed through the node screening mechanism, and the later the artificial potential field method is introduced to ensure that a safe distance is always maintained from the unknown obstacles present in the re-planning process. At the same time, this research study adopts the method of setting virtual target points to solve the local extreme value problem that may be encountered in the actual movement of the machine. For developing an efficient and intelligent path planning model, the computer vision should be referred. The binocular recognition is equipped with two symmetrical signal acquisition cameras, which can realize the positioning of the status information. The enhanced theoretical vision algorithm is then combined for performing systematic optimization. The performance is validated by testing it on different datasets.
基于计算机视觉识别算法的智能机器人路径规划模型
本研究设计了一种基于计算机视觉识别算法的智能机器人路径规划模型。其中,通过节点筛选机制去除预先规划路径中存在的冗余节点,而后引入人工势场法,确保重新规划过程中始终与未知障碍物保持安全距离。同时,本研究采用设置虚拟目标点的方法,解决了机器实际运动中可能遇到的局部极值问题。为了建立一个高效、智能的路径规划模型,需要参考计算机视觉。双目识别配备了两个对称的信号采集摄像头,可以实现状态信息的定位。然后结合改进的理论视觉算法进行系统优化。通过在不同的数据集上进行测试,验证了性能。
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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