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Depthmap-based obstacle avoidance on rough terrain

机译:在粗糙地形上基于深度图的避障

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It is an important and difficult task for a mobile robot to detect the maneuverable area and to avoid obstacles. Numerous methods using ultra sonic or infrared sensors have been successfully proposed and adapted to various robots. These robots, however, cannot move around in unleveled areas because their sensors are incapable of measuring in a three-dimensional (3D) environment. Some obstacle avoidance methods using 3D sensors were proposed. It is a problem to move the robot around smoothly and continuously, considering that these methods require numerous processing steps and time to determine the obstacles and the avoidance path. In this paper, a new obstacle avoidance method using a depthmap is proposed that applies 3D sensor technology to autonomous exterior robot systems. Employing this method the robot is able to recognize the obstacle continuously and thus can be used on rough terrain. All processes in the algorithm handle images without the environmental model. In recent years, a sensing device used for laser modules or CCD cameras that can sense 3D space in real-time have been developed. Using such a sensor in conjunction with the proposed method, the test unit and autonomous vehicle were built to evaluate the methodology in an outdoor environment These units were able to detect the obstacle, avoid it, and Iocomote autonomously on rough terrain. As a result, this method has the advantage of robustness on rough terrain, and an autonomous mobile robot with this test unit is capable of navigation on an unleveled road.
机译:对于移动机器人而言,检测可操纵区域并避免障碍是一项重要而艰巨的任务。已经成功地提出了使用超声波或红外传感器的多种方法,并适用于各种机器人。但是,由于这些机器人无法在三维(3D)环境中进行测量,因此它们无法在未平整的区域中移动。提出了一些使用3D传感器的避障方法。考虑到这些方法需要大量的处理步骤和时间来确定障碍物和避免路径,因此使机器人平稳连续地移动是一个问题。在本文中,提出了一种新的使用深度图的避障方法,该方法将3D传感器技术应用于自主的外部机器人系统。使用这种方法,机器人可以连续识别障碍物,因此可以在崎terrain的地形上使用。该算法中的所有过程都无需环境模型即可处理图像。近年来,已经开发了用于激光模块或CCD相机的可以实时感测3D空间的感测设备。将这种传感器与所提出的方法结合使用,可以构建测试单元和自动驾驶车辆,以评估室外环境中的方法。这些单元能够检测,避开障碍物,并在崎terrain的地形上自动进行障碍物识别。结果,该方法具有在崎terrain地形上鲁棒性的优点,并且具有该测试单元的自主移动机器人能够在不平坦的道路上导航。

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