融合超宽带方位和距离的移动机器人定位

可靠定位是机器人完成导航和路径规划的前提,机器人通过多个超宽带(ultra-wideband, UWB)基站的测距信息实现定 位,但基站数量不足时定位精度受限。 针对这一问题,提出融合超宽带距离和方位的移动机器人定位方法。 根据方位标准差区 分信号来自基站前方(视场)或背后(非视场),消除方位的前后奇异性。 在此基础上,利用 UWB 距离和方位测量值构建约束函 数,通过图优化算法融合里程计和 UWB 测量数据实现全局位姿优化。 实验结果表明,该方法在 13 m×6 m 的室内环境中,移动 机器人无规则运动能够达到 0. 093 m 的定位精度,比传统的基于测距 UWB 和里程计融合方法定位性能提升了 46%,且具有较 强的鲁棒性。

Mobile robot localization based on ultra-wideband bearing and ranging

Reliable localization is a crucial prerequisite for robots to perform navigation and path planning. Traditionally, locations of robots are derived from the ranging measurements between ultra-wideband (UWB) tag and anchors, results with poor accuracy may be yielded when available anchors are insufficient. To tackle this issue, a mobile robot localization method based on ultra-wideband bearing and range is proposed. Firstly, the direction of the UWB tag, i. e. , the forward field of view ( FOV) or behind non-field of view (NFOV) of the anchor, is determined according to the standard deviation of the UWB bearing signal, thus eliminating the front-back singularity in the robot localization process. In addition, constraint functions are constructed utilizing UWB range and bearing measurements, and global pose optimization is achieved by fusing odometry and UWB measurements through a graph-based optimization algorithm. The experiment results show that the proposed method has strong robustness and is able to locate the irregularly moving robot with a localization accuracy of 0. 093 m in a 13 m×6 m indoor environment, which is 46% better than the traditional localization method based on ranging UWB and odometry fusion.