首页 /研究 /Using an extended Kalman filter for relative localisation in a moving robot formation
SWARM

Using an extended Kalman filter for relative localisation in a moving robot formation

Frank Schneider, Dennis Wildermuth

发表年份
2004
引用次数
15

摘要

This work presents a new approach to relative position estimation in multi robot systems. The information of laser scanner systems is used to estimate the relative positions between each other. An extended Kalman filter (EKF) is used to combine this information into one continuously updated position estimation. All robots of a group use these data in order to generate one common coordinate system. Experimental results are presented including formation movement as an example application.

关键词

Extended Kalman filterKalman filterRobotPosition (finance)Computer scienceComputer visionArtificial intelligenceCoordinate systemFast Kalman filterInvariant extended Kalman filter

相关论文

查看 SWARM 分类全部论文