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Vision-Based Obstacle Avoidance of Mobile Robot Using Quantized Spatial Model | Science Publications

机译:量化空间模型的移动机器人基于视觉的避障技术科学出版物

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> Problem statement: Problem of moving a robot through unknown environment has attracted much attention over past two decades. Such problems have several difficulties and complexities that are unobserved, besides the ambiguity of how this can be achieved since a robot may encounter obstacles of all forms that must be bypassed in an intelligent manner. This research had been aimed to develop a system that was able to detect obstacles in a mobile robot's path using a single camera as only sensory input and to achieve the target point in optimized manner. For this reason, algorithm which took total path length and safety into account was developed. Approach: To control movement of robot from a starting to a target point inside the site where obstacles can obstruct the way of robot, real-time software-specially tailored for this purpose-was necessary to develop. To analyze and to process scene images captured by a (vision) camera, camera was installed at the top over the center of site in a way that it covered whole site through which sufficient image information could be delivered. From sequentially captured images that was manipulated through image processing and computer vision, the system built a representative site model, whose ingredients were gridded squares as a result of quantized spatial plane of site and then it began planning the desired routing path. Results: For building a robot path, less computing effort was necessary because grid information was much easier to deal with than pixels and only a minimum amount of stored data of symbolic site model from current and previous state was necessary. Conclusion: Using a quantized spatial domain, a less computational effort was necessary to control movement of robot with the ability of obstacle detection and avoidance.
机译: > 问题陈述:在过去的二十年中,使机器人穿越未知环境的问题引起了很多关注。除了机器人如何可能遇到各种形式的障碍,这些问题还有许多困难和复杂性,这些困难和复杂性是无法解决的,因为机器人可能会遇到必须以智能方式绕过的各种形式的障碍。这项研究的目的是开发一种系统,该系统能够仅使用单个摄像头作为感官输入来检测移动机器人路径中的障碍物,并以最佳方式实现目标点。因此,开发了考虑总路径长度和安全性的算法。 方法:为了控制机器人从起点到障碍物可能妨碍机器人前进的位置内的目标点的移动,需要开发专门为此目的而定制的实时软件。为了分析和处理(视觉)摄像机捕获的场景图像,将摄像机安装在站点中心上方的顶部,以使其覆盖整个站点,从而可以传递足够的图像信息。从通过图像处理和计算机视觉处理的顺序捕获的图像中,系统建立了一个代表性的站点模型,由于站点空间空间的量化,其成分被网格化为正方形,然后开始规划所需的路由路径。 结果:对于构建机器人路径,需要较少的计算工作量,因为网格信息比像素更容易处理,并且仅需要最少数量的来自当前和先前状态的符号站点模型的存储数据。 结论:使用量化的空间域,只需较少的计算量即可控制机器人运动并具有障碍检测和躲避的能力。

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