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Onboard optical flow and vision based localization for a quadrotor in unstructured indoor environments

Qingji Gao, Yao Wang, Dandan Hu

发表年份
2014
引用次数
3

摘要

This paper considers problem of localization for an aerial robot in unstructured indoor environments. A vision correction method based on linear characteristics is proposed. The dynamic model is established using an optical flow sensor. Use a strap-down camera to capture the frame of perpendicular line on the ground, and calculate the global position of their intersection point. As an observation, the vision position is input to the KALMAN filter in order to eliminate the accumulated error. Experimental results from indoor hover test verified the accuracy and real-time of the approach.

关键词

Computer visionComputer scienceOptical flowArtificial intelligenceIntersection (aeronautics)Frame (networking)Position (finance)Kalman filterRobotExtended Kalman filter

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