Visual landing pose estimation method of rotary wing type unmanned aerial vehicle

Abstract

The invention provides a visual landing pose estimation method of a rotary wing type unmanned aerial vehicle. According to the method, a Tsai method and a fast four-point method are combined to calculate pose parameters; with the combination mode adopted, time consumption of iterative solution in the Tsai method can be avoided, the accuracy of pose parameter calculation in the Tsai method and the fast four-point method can be improved; a hierarchical cooperation target is designed based on the method, and the target can be applicable to pose estimation under different landing heights; and a large number of simulation experiments are carried out to perform method validation.

Description

technical field [0001] The invention belongs to the field of unmanned aerial vehicle control, and relates to a visual landing pose estimation method of a rotary-wing unmanned aerial vehicle. Background technique [0002] Rotary-wing UAVs can achieve vertical take-off and landing, free hovering, low-altitude and low-speed flight and other flight modes, and have the advantages of low cost, low power consumption, and flexible response. These advantages make it widely used in the fields of service and rescue in complex environments. Among the four stages of take-off, cruising, hovering, and landing of the UAV, landing is the most important link. At present, the autonomous landing navigation systems of rotor UAVs mainly include GPS / INS navigation systems, visual navigation systems, and multi-sensor fusion navigation systems. Among them, the accuracy of positioning, navigation and landing using GPS / INS and other signals is not high, and GPS signals cannot be used in indoor and o...

AI Technical Summary

Problems solved by technology

Different pose estimation methods have deficiencies in time and accuracy. For example, the literature uses the RAC-based camera calibration method proposed by Tsai to calculate the pose parameters of the UAV. This method needs to solve the optimal solution in an iterative process, and usually It is to find the local optimal solution, so the estimation accuracy and time efficiency of the position parameters are not high; the literature designs the icon of the classification strategy, and uses the fast four-point method to realize the 3D pose estimation, which can realize the fast solution of the pose parameters, And the height calculation accuracy is high, and the required features are less, but the calculation accuracy of the attitude angle is insufficient

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