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A Flying Robot Localization Method Based on Multi-Sensor Fusion

Changan Liu, Sheng Zhang, Hua Wu, Ruifang Dong

Year
2014
Citations
2

Abstract

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.

Keywords

Computer scienceComputer visionRobustness (evolution)Inertial measurement unitArtificial intelligenceFuse (electrical)Global Positioning SystemSensor fusionKalman filterCoordinate system

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