为多个ugv构建配置空间

Jiao Linan, Zhenmin Tang
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引用次数: 0

摘要

在障碍物是静态的,机器人具有全局环境知识的假设下,通常使用经典构型空间(c空间)。近年来,多机器人系统受到越来越多的关注,但具有局部传感的多机器人系统不能满足这一假设。如果可以求解,则MRS的运动规划将受益于c空间中先前的运动规划算法。为了解决上述问题,首先,我们将环境和机器人建模为几组多边形,机器人是无人驾驶地面车辆(ugv),具有有限的传感范围,并且可以相互通信。然后介绍了一种分散的方法,即两个自主机器人搜索环境并建立c空间障碍物,每隔一定的时间间隔交换和合并另一个机器人生成的部分c空间,直到建立整个c空间障碍物,这种方法类似于并行映射和定位(CML),但我们主要关注c空间的生成和合并算法。最后通过仿真实现验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building configuration space for multiple UGVs
Classical configuration space (C-space) is often used in such a assumption that obstacles are static and robots have global knowledge of environment. Recently, there has been much more attention in multi-robot systems (MRS), unfortunately a MRS which have local sensing cannot meet the assumption. If it can be solved, the motion planning of the MRS benefits from previous motion planning algorithms in C-space. Toward resolving aforementioned problems, in the first place, we model the environment and robots as some sets of polygons, robots are unmanned ground vehicles (UGVs) with limited sensing range and can communicate with each other. Then a decentralized method is introduced by which two autonomous robots search environment and build C-space obstacles, while exchange and merge partial C-space generated by another robot every certain time interval until the whole C-space obstacles are established, it is similar to concurrent mapping and localization (CML), but we mainly focus on the algorithm of generating and merging C-space. Finally a simulated implementation demonstrates validity of our algorithm.
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