Visual Localization of Inspection Robot Using Extended Kalman Filter and Aruco Markers
2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)(2018)
摘要
This paper investigates a localization technology based on Aruco Markers for substation inspection robot. Extended Kalman Filter(EKF) algorithm is used to fuse odometer information and camera measurement data from detection of Aruco markers. The experiment results show that the localization problem can be solved by EKF localization based on Aruco markers efficiently. The localization algorithm can provide the inspection robot with relatively accurate position information and shield the impact of the dynamic environment.
更多查看译文
关键词
Conferences,Robots,Biomimetics,Voltage control
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要