Cooperative Localization in Unknown Environment towards Multi-Robot Systems
作者单位：School of Control Science and Engineering Shandong University Engineering Research Center of Intelligent Unmanned System Ministry of Education
会议名称：《第43届中国控制会议》
会议日期：1000年
学科分类：080202[工学-机械电子工程] 08[工学] 0804[工学-仪器科学与技术] 0802[工学-机械工程]
基 金：supported in part by the National Natural Science Foundation of China (Grant No. 62373221) in part by the Shandong Provincial Natural Science Foundation for Distinguished Young Scholars(Grant No. ZR2022JQ28) the Key Development Pro gram for Basic Research of Shandong Province under Grant ZR2019ZD07
关 键 词：Multi-Robot Systems Relative Localization Cooperative Localization GPS-denied environment Cubature Kalman Filtering
摘 要：Localization plays an important role in robotics, aiming at the problem of multi-robot cooperative localization in a GPS-denied environment, a multi-sensor fusion cooperative localization method based on relative observations is presented in this paper. The relative observation module is comprised primarily of a monocular camera and an ultra-wideband(UWB),which associates visual detection with UWB distance measurement data to obtain relative measurement models for multi-robot systems. An Extended Cubature Kalman Filter(ECKF) is designed to fuse observations and internal sensor odometry data to improve system accuracy and robustness. The algorithm deploys on a single robot, with a fleet of sharing relative *** evaluate the performance of the proposed method, we conduct the experiment in the Gazebo simulation environment and the cooperative localization experiment is carried out on three unmanned robots in the real world. Comparing the global camera position as the ground truth, the results show the accuracy and robustness of our system.