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An integrative approach for path planning and tracking of a shape-aware mobile robot in structured environment using vision sensor

机译:使用视觉传感器的结构化环境中的形状感知移动机器人的路径规划和跟踪综合方法

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A shape-aware path planning algorithm is necessary for real-time execution of a task by a mobile robot whereas path planning algorithms available in literature consider mobile robot as a point object. Current work proposes a shape-aware A* path planning approach with a heuristic function to accommodate the shape of mobile robot. In this paper, the detection, tracking and control of the robot has been carried out for the mobile robot while performing a task in a structured environment. For the implementation and validation, an overhead camera is used to capture the images of obstacles in the task space and published in ROS platform. The captured images are also processed using OpenCV software for detection and tracking using Kanade-Lucas-Tomasi (KLT) and Kalman filter algorithms for different test scenarios. The proposed approach accurately detects and tracks the shape aware mobile robot with percentage error ranging from 6%-10% in different cases.
机译:形状感知路径规划算法是通过移动机器人实时执行任务的必要条件,而文献中可用的路径规划算法将移动机器人视为点对象。 目前的工作提出了一种形状感知的A *路径规划方法,具有启发式功能以适应移动机器人的形状。 在本文中,在在结构化环境中执行任务的同时,已经为移动机器人进行了检测,跟踪和控制。 为了实现和验证,使用架空相机用于捕获任务空间中的障碍图像并在ROS平台上发布。 还使用OpenCV软件处理捕获的图像,用于使用Kanade-Lucas-Tomasi(KLT)和Kalman滤波器算法进行检测和跟踪不同的测试场景。 所提出的方法准确地检测并跟踪形状的感知移动机器人,在不同情况下,百分比误差为6%-10%。

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