智能巡检机器人系统设计与实现
首发时间:2018-08-15
摘要:针对灾后地形复杂、危险系数大的特点,提出一种基于视觉识别的智能巡检机器人控制系统。文中采用高性能的ARM微处理芯片作为核心器件,设计了四轮驱动移动机器人的底层运动控制系统。通过加装图像传感器、速度检测器实现对机器人的行驶路线、速度状况的实时测量与控制,给出了系统相应的硬件设计方案及软件控制算法。重点提出一种改进的杂交粒子群优化算法来实现FIR低通滤波器,从而滤除视频图像的低频噪声,再对图像进行二值化处理以提取目标特征。实验证明,通过对系统的硬件及智能控制算法的设计,该智能机器人能够在给定的区域内完成自主循迹,随着导轨路径的改变能够调整自身运行方向和运行速度,满足设计要求。
关键词: 模式识别与智能系统 视觉识别 杂交粒子群优化算法 自主循迹
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Design and implementation of intelligent inspection robot system
Abstract:In view of the complicated terrain and large danger coefficient after disaster, an intelligent inspection robot control system based on visual recognition is proposed. In this paper, a high-performance ARM microchip is used as the core device, and the bottom motion control system of the four wheel drive mobile robot is designed. By adding the image sensor and speed detector, the real-time measurement and control of the driving route and speed condition of the robot are realized, and the corresponding hardware circuit design and software control algorithm of the system are given. An improved hybrid particle swarm optimization (MPSO) algorithm is proposed to implement the FIR low pass filter to filter the low frequency noise of the video image, and then two values of the image are processed to extract the target features. The experiment shows that by designing the hardwareand intelligent control algorithm of the system, the intelligent robot can complete the independent tracking in a given area. With the change of the track path, its direction and speed can be adjusted and the design requirements are met.
Keywords: Pattern recognition and intelligent system Visual recognition Hybrid particle swarm optimization algorithm Intelligent path-recognize
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