基于UWB方位的机器人间相对定位

Relative localization between robots based on UWB bearing

相对定位是实现多机器人编队、探索救援等协作任务的前提。针对卫星信号受阻、未知无基础设施环境中机器人间的相对定位问题,提出一种基于超宽带(ultra-wideband,UWB)方位的相对定位方法。利用滑动窗口截取一段时间内机器人间观测方位和运动轨迹,构建方位代价函数,通过最小化代价函数估计机器人间的相对位姿。然而,函数的非凸性导致传统优化算法陷入局部最优解,因此,采用麻雀搜索算法(SSA)对代价函数进行求解,实现机器人间的相对定位。为减少UWB方位测量误差对定位结果的影响,通过后端图优化算法融合SSA估计位姿和里程计信息,实现更加精准的相对定位。实验结果表明,该方法在12 m×6 m的室内环境中,能够达到0.32 m的平均位置误差以及2.1°的平均旋转误差。

Relative localization is a prerequisite for multiple robots in unknown environments to accomplish collaborative tasks such as formation,exploration,and rescue.A relative localization method based on ultra-wideband(UWB)bearing is proposed for positioning between robots in unknown infrastructure-free environments where satellite signals are blocked.The proposed method uses a sliding window to intercept the inter-robot bearing observations and motion trajectories over a period of time,construct the bearing cost function,and estimate the relative pose between the robots by minimizing the cost function.However,the non-convexity of the function leads traditional optimization algorithms to fall into local optimal solutions.Therefore,sparrow search algorithm(SSA)is used to optimize the cost function for the relative localization between robots.To reduce the effect of UWB bearing measurement errors,the SSA-estimated pose and odometry information are fused by a back-end pose graph optimization algorithm to achieve more accurate relative positioning.The experimental results show that the method is able to achieve an average translation error of 0.32 m and an average rotation error of 2.1°in an indoor environment with a size of 12 m×6 m.