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Adaptive coverage control in non-convex environments with unknown obstacles

机译:障碍物未知的非凸环境中的自适应覆盖控制

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This paper presents an adaptive control law which enables a team of mobile robots to navigate in a non-convex environment in the presence of unknown obstacles. The proposed approach relies on potential field method, adaptive control techniques and Voronoi-based decomposition. Each agent in the network tasked with starting from random initial positions and navigating to learn regions within the area with greatest importance and concentrate their coverage on these areas while avoiding collisions with the obstacles. In particular, our presented methodology is able to deal with scenarios where a priori knowledge of the search domain is not available and when the navigation region contains unknown obstacles. Simulation results are presented to validate the enhanced performance of the proposed approach.
机译:本文提出了一种自适应控制定律,该定律使一组移动机器人能够在存在未知障碍物的非凸面环境中导航。所提出的方法依赖于势场方法,自适应控制技术和基于Voronoi的分解。网络中的每个代理都负责从随机的初始位置开始导航,以了解该区域内最重要的区域,并将其覆盖范围集中在这些区域上,同时避免与障碍物发生碰撞。特别地,我们提出的方法能够处理其中搜索域的先验知识不可用以及导航区域包含未知障碍的情况。仿真结果被提出来验证所提出方法的增强性能。

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