Open AccessA Flying Robot Localization Method Based on Multi-Sensor Fusion
Author(s) -
Changan Liu,
Sheng Zhang,
Hua Wu,
Ruifang Dong
Publication year - 2014
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/58927
Subject(s) - computer science , computer vision , robustness (evolution) , inertial measurement unit , artificial intelligence , fuse (electrical) , global positioning system , sensor fusion , kalman filter , coordinate system , robot , fusion , simultaneous localization and mapping , mobile robot , telecommunications , biochemistry , chemistry , linguistics , philosophy , electrical engineering , gene , engineering
This paper proposes a novel localization method for a power-tower-inspection flying robot based on fusion of vision, IMU and GPS. First, the research background is introduced in relation to a visual localization algorithm derived from 3D-model-based tracking and a coordinate transformation model for related coordinate frames. Then, a multi-sensor fusion-based localization method is presented, in which two collaborative Kalman filters are designed to fuse IMU/GPS and visual information. Finally, experimental results are presented to show the robustness and precision of the proposed method