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Behavior based complete coverage task of unknown area by an autonomous mobile robot scorpion with static obstacles in environment

机译:环境中具有静态障碍的自主移动机器人蝎基于行为的未知区域完全覆盖任务

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In the paper the behavior based control system of an autonomous mobile robot SCORPION is presented to execute the one of the most difficult navigation task, which is the complete coverage task of unknown area with static obstacles in the environment. The main principle assumed to design control system was that the robot should cover all area only once, if it possible, to optimize the length of path and energy consumption. All commercial robots like Roomba, Trilobite or IVO move using structured templates combined with random movement. Therefore the path of coverage is not optimal - directions of movement are often chosen randomly, so robot covers the same area many times wasting time and energy. In paper the five main developed templates of movement were described to fulfill main task in ordered manner using primarily "the way of the ox" template of coverage [1, 2, 5, 10]. The behavioral control system is implemented in a computer application written in Python [5]. In the paper the test methodology of the developed system on real mobile robot ERSP SCORPION equipped with IR sensors is presented. Graphical and quantitative results of tests of accomplishment of complete coverage task are given for 6 different configurations of obstacles in the robot's environment. Conclusions are presented and discussed [5]. Ways to improve the quality indicators [1,2] of the task of complete coverage of a unknown area are also showed.
机译:本文提出了一种基于行为的自主移动机器人SCORPION控制系统,以执行最困难的导航任务之一,这是在环境中具有静态障碍物的未知区域的完全覆盖任务。设计控制系统的主要原则是,机器人应尽可能覆盖所有区域一次,以优化路径长度和能耗。所有商用机器人(如Roomba,Trilobite或IVO)都使用结构化模板结合随机移动来移动。因此,覆盖的路径不是最佳的-运动方向通常是随机选择的,因此机器人多次覆盖同一区域会浪费时间和精力。在本文中,描述了五个主要开发的运动模板,这些运动模板主要使用覆盖率[1、2、5、10]的“牛的方式”模板有序地完成了主要任务。行为控制系统在用Python [5]编写的计算机应用程序中实现。本文介绍了在配备红外传感器的真实移动机器人ERSP SCORPION上开发的系统的测试方法。给出了机器人环境中6种不同配置的障碍物完成覆盖任务的测试的图形和定量结果。结论被提出和讨论[5]。还显示了改善完全覆盖未知区域任务的质量指标[1,2]的方法。

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