Sensor-Fusion Based Navigation for Mobile Robot in Outdoor Environment

Muhammad Yousaf Ali Khan, E. Mustafa, A. Nawaz, N. Saleem, U. Illahi
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Abstract

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.
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基于传感器融合的户外移动机器人导航
车辆或机器人的自主导航是目前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。考虑到这一点,提出了一种室外环境下移动机器人自主导航算法。这条导航轨道由包含障碍物的彩色边界和一些未规划的表面以及GPS(全球定位系统)警报的一些特定点组成。主要目标是避免彩色边界和障碍物。对于视觉问题,使用网络摄像头。首先,使用OpenCV库通过HSI(色调饱和强度)技术检测彩色边界。首先利用Canny边缘算法找到边界的两边,然后利用Hough变换检测轨道两侧的直线。最后,检测出最近的边界线,并计算出其中心点,移动机器人必须转向以避开该边界线。第二步是避障,由激光测距仪(Laser Range Finder, LRF)来完成避障,首先定义LRF的范围,因为不是所有的障碍物都需要避障,只要在之前定义的指定范围内检测到并避开障碍物,最后使用GPS接收机在特定点发出报警。实现了移动机器人在室外环境下的成功导航。
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