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Sensor-Fusion Based Navigation for Mobile Robot in Outdoor Environment

机译:基于传感器融合的户外环境的移动机器人导航

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摘要

Autonomous navigation of the vehicles or robots is very challenging and useful task used by many scientists and researchers these days. By keeping this fact in mind, an algorithm for autonomous navigation of mobile robot in outdoor environment is proposed. This navigation track consists of colored border containing obstacles and some unplanned surfaces along with some specific points for GPS (Global Positioning System) alarms. The main goal is to avoid colored border and obstacles. For the vision problem webcam is used. First the colored border is detected by using OpenCV library by following HSI (Hue Saturation Intensity)technique. The Canny edge algorithm is used to find both edges of the border, then for detecting straight lines on both sides of track, Hough transformation is used. Finally, the closest border line is detected and its center point is calculated for which the mobile robot has to steer to avoid it. Second step is to avoid the obstacles, which is done by LRF (Laser Range Finder), first the range of LRF is defined, because not all obstacles have to be avoided, only those obstacles are detected and avoided which are in specified range as defined before, and finally GPS receiver is used to make alarms at some specific points. As a result, a successful navigation of the mobile robot in the outdoor environment is implemented.
机译:汽车或机器人的自主导航是许多科学家和研究人员使用的非常具有挑战性和有用的任务。通过掌握这一事实,提出了一种用于在室外环境中移动机器人的自主导航算法。该导航轨道由彩色边框包含障碍物和一些未约会表面以及GPS(全球定位系统)警报的一些特定点。主要目标是避免彩色边框和障碍物。对于愿景问题,使用网络摄像头。首先,通过遵循HSI(色调饱和强度)技术来检测彩色边界。 Canny Edge算法用于找到边界的两个边,然后用于检测轨道两侧的直线,使用Hough变换。最后,检测到最接近的边界线,并计算其中心点,移动机器人必须转向避免它。第二步是避免由LRF(激光测距仪)完成的障碍物,首先定义了LRF的范围,因为不必避免所有障碍物,只有那些障碍物被检测到,避免了定义的指定范围内的障碍物之前,最后GPS接收器用于在某些特定点处发出警报。结果,实现了在室外环境中的移动机器人的成功导航。

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