基于相对方位的多机器人合作定位算法

Multi-Robot Cooperative Localization Based on Relative Bearing

研究了在未知环境中,利用扩展卡尔曼滤波方法融合内部传感器信息与机器人之间的相对方位观测量,同时定位队列中每个机器人的问题.通过机器人队列共享相对方位观测量,融合不同平台感知的信息,可有效地提高整个队列的定位精度.分析了该方法与机器人分布和运动的关系及存在的缺陷,针对这一问题,提出了改进措施,从而使该方法的可靠性和实用性得到增强.仿真实验验证了改进方法的有效性.

We study the problem of Multi-Robot Simultaneous Localization in an unknown environment based on relative bearings with EKE. Relative bearings from different robots are shared among members of the team. Localization accuracy of robot group can be improved obviously by fusing relative bearings. We analyse the situations about relative position of the robots and their motion trajectories, which easily produce not-converged results. We present an improved method to overcome the fault. The robust and practicability of localization are greatly increased. Simulation results prove the method is effective in dealing with the cooperative localization problem.