基于tinySLAM的nano-UAV集群探索
tinySLAM-based exploration with a swarm of nano-UAVs
AI总结：
本文研究nano-UAV集群的SLAM与探索问题，采用tinySLAM算法建图并结合改进的动态覆盖算法进行路径规划，在硬件受限的Crazyflie 2.1平台上实现了稳定的环境探索。
摘要：
本文研究nano-UAV集群的SLAM与探索问题。采用基于激光测距仪的tinySLAM算法构建环境地图，并利用迭代最近点算法同步地图。随后，UAV通过驶向由改进的动态覆盖算法选择的点来探索地图，我们为该算法证明了稳定性结论。两种算法相互提供信息，使UAV能够测绘环境的新区域并进入其中进行探索。本文展示了使用nano-UAV Crazyflie 2.1平台的实验结果。一个关键挑战是在硬件受限的实验平台上实现所有算法。
英文摘要：
This paper concerns SLAM and exploration for a swarm of nano-UAVs. The laser range finder-based tinySLAM algorithm is used to build maps of the environment. The maps are synchronized using an iterative closest point algorithm. The UAVs then explore the map by steering to points selected by a modified dynamic coverage algorithm, for which we prove a stability result. Both algorithms inform each other, allowing the UAVs to map out new areas of the environment and move into them for exploration. Experimental findings using the nano-UAV Crazyflie 2.1 platform are presented. A key challenge is to implement all algorithms on the hardware limited experimental platform.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
