首页> 外文会议>IEEE/RSJ International Conference on Intelligent Robots and Systems;IROS 2009 >A dynamic path planning approach for multi-robot sensor-based coverage considering energy constraints
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A dynamic path planning approach for multi-robot sensor-based coverage considering energy constraints

机译:考虑能量约束的基于多机器人传感器的覆盖范围的动态路径规划方法

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In this study, a novel dynamic path planning approach is proposed for multi-robot sensor-based coverage considering energy capacities of the mobile robots. The environment is assumed to be narrow and partially unknown. A Generalized Voronoi diagram-based network is used for the sensor-based coverage planning due to narrow nature of the environment. On the other hand, partially unknown nature is handled with proposed dynamic re-planning approach. Initially, the robots are assumed to be at the same depot with equal initial energy capacities. In this case, an initial complete coverage route is constructed considering robot energy capacities using classical capacitated arc routing problem (CARP) approach with some minor modifications related to coverage problem. But, due to partially unknown nature, the robots may face with blockage on routes, and a fast re-planning is required which considers remaining energy capacities and current positions of the robots. So, new plan is obtained by a modifying Ulusoy's algorithm that was developed for classical CARP. The developed algorithm is coded in C++ and implemented on P3-DX mobile robots in MobileSim simulation environment.
机译:在这项研究中,提出了一种新颖的动态路径规划方法,该方法考虑了移动机器人的能量,可用于基于多机器人传感器的覆盖范围。假定环境狭窄且部分未知。由于环境的狭窄性,将基于广义Voronoi图的网络用于基于传感器的覆盖范围规划。另一方面,通过提议的动态重新规划方法可以处理部分未知的性质。最初,假定机器人位于具有相同初始能量容量的相同仓库中。在这种情况下,使用经典的电容弧形布线问题(CARP)方法并考虑到与覆盖问题相关的一些较小修改,从而在考虑机器人能量的情况下构建初始的完整覆盖路线。但是,由于部分未知的性质,机器人可能会在路线上遇到障碍,因此需要进行快速重新规划,其中要考虑到机器人的剩余能量和当前位置。因此,通过修改为经典CARP开发的Ulusoy算法获得了新的计划。所开发的算法用C ++编码,并在MobileSim仿真环境中的P3-DX移动机器人上实现。

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