基于遗传算法的拆弹机器人自主定位与映射

M. F. Hamza
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引用次数: 0

摘要

随着科技的进步,警察和军事人员开始依靠技术来执行过去需要人工干预的任务。探测汽车下的炸弹已经成为警察和军事人员在执行保护重要人物免受炸弹威胁任务时的例行公事之一。本文对车辆底盘的定位、导航和测绘进行了仿真研究。导航仿真包括周界导航、路径规划和人工威胁搜索。周边导航导航车辆的周边,为威胁搜索构建边界条件。路径规划允许自动威胁搜索,并使用三种不同的方法在车辆周长内生成的随机点上构建路径。方法有启发式(贪心法)、遗传算法和遗传算法优化启发式。手动威胁搜索允许用户在车辆周边范围内定义搜索区域。车辆底盘的测绘是在使用距离传感器扫描车辆底盘的同时,对车辆下方进行扫描。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GA Based Autonomous Self Localization and Mapping for Bomb Disposal Robot
With the advancement of technology, the police and military personnel begin to rely on technology to perform tasks which in the past require manual intervention. Detecting bomb under the car has been one of the routines for police and military personnel during their mission to protect important individual from bomb threat. In this study, the localization, navigation and mapping of vehicle undercarriage are simulated. Navigation simulation includes the perimeter navigation, path planning and manual threat search. Perimeter navigation navigates the perimeter of the vehicle to construct a boundary condition for threat search. Path planning allows for automated threat search and three different methods were used to construct the path on random spot generated within the perimeter of the vehicle. The methods are heuristic (Greedy Method), GA, and GA optimized heuristic. Manual threat search allows user to define search area within the perimeter of the vehicle. Mapping of vehicle undercarriage is done by sweeping under the vehicle while scanning the undercarriage of the vehicle using distance sensor.
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