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Global Path Planning and Path-Following for Wheeled Mobile Robot Using a Novel Control Structure Based on a Vision Sensor

机译:使用基于视觉传感器的新型控制结构的轮式移动机器人的全局路径规划和路径跟踪

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This paper presents a novel design for the kinematic control structure of the wheeled mobile robot (WMR) path planning and path-following. The proposed system is focused on the implementation of practical realtime model-free algorithms based on visual servoing. The mainframe of this study is to implement a novel kinematic control structure based on visual sevoing and hybrid algorithms in real-time mobile robot applications. First, the structure of the proposed algorithm based on the visual information extracted from an overhead camera has been addressed. Then, the classification process of robot position and orientation, target, and obstacles has been addressed. Second, the path planning algorithms' initial parameters and obstacles-free path coordinates have been determined by visual information extracted from images in real time. In this step, the interval type-2 fuzzy inference (IT2FIS) algorithm and various algorithms used in path planning have been compared and their performances have been analyzed. The third stage handled the path-following process using a novel control structure for keeping up the robot on the generated path. In this step, the proposed approach is compared with fuzzy Type-l/Type-2 and fuzzy-PID control algorithms, and their results have been analyzed statistically. The proposed system has been successfully implemented on several maps. The experimental results show that the developed design is valid in generating collision-free paths efficiently and consistently and able to guide the robot to follow the path in real time.
机译:本文介绍了轮式移动机器人(WMR)路径规划和路径跟随的运动控制结构的新颖设计。该制定的系统专注于基于视觉伺服的实际实时模型无模型算法的实现。本研究的主机是基于实时移动机器人应用中的视觉七分和混合算法的新型运动控制结构。首先,已经解决了基于从开销相机提取的视觉信息的所提出的算法的结构。然后,已经解决了机器人位置和方向,目标和障碍的分类过程。其次,通过实时从图像中提取的视觉信息确定了路径规划算法的初始参数和无障碍路径坐标。在该步骤中,已经进行了比较了间隔类型-2模糊推理(IT2FIS)算法和用于路径规划中使用的各种算法,并分析了它们的性能。第三阶段使用新的控制结构处理路径以下过程,以便在所生成的路径上保持机器人。在该步骤中,将所提出的方法与模糊类型-L /类型-2和模糊PID控制算法进行比较,并且它们的结果已经在统计上进行了分析。建议的系统已成功在几张地图上实施。实验结果表明,开发的设计在有效且一致地和能够将机器人实时跟踪路径,有效地产生无碰撞路径。

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