Position Tracking And Attitude Estimation Of An Indoor Quadrotor Based On Kinect

With the development of miniaturization and lightness of quadrotor drones,and because of their low price,drones have been widely used in entertainment and service areas.In recent years,the research on quadrotors has developed rapidly,but it is still unable to achieve complete autonomous flight.At present,how to construct a simple and easy to implement autonomous flight tracking system has become a research hotspot.Due to the weak indoor GPS signal,the indoor tracking positioning and attitude acquisition of the quadrotor became a difficult point in the autonomous flight control system of the indoor four-rotor quadrotor.Compared with the quadrotor positioning and tracking system built by hundreds of thousands of dollars,the system based on low-cost Kinect depth camera has more scientific research value and application prospects.The quadrotor positioning and tracking system is mainly divided into two parts:the marking and identification of the quadrotor,the positioning of the quadrotor and the estimation of the attitude.In the marking and identification method of indoor drones,this paper proposes ArUco markers for quadrotor marking to improve tracking and attitude estimation accuracy.At the same time,the positioning and attitude estimation of the quadrotor are realized by the color image and depth image of the Kinect camera.Finally,based on microwave communication,this paper realizes the flight process of autonomous ly controlling the drone’s take-off,hovering,simple avoidance and landing.The main research work and results of this paper are as follows:1.The ArUco quadrotor marking algorithm based on virtual reality(AR)technology is proposed.In order to analyze and compare the accuracy of the positioning and attitude estimation of the method,a small indoor quadrotor multi-marker(including the ArUco drone marking and the currently widely used color space domain marking)is designed and implemented.2.This paper analyzes and compares the detection rate,tracking accuracy and real-time performance of the two marking methods in different spatial brightness,different spatial color complexity,and different ranging conditions.The experimental results show that the detection rate,tracking real-time performance,attitude estimation accuracy and robustness of the U-marker in the complex environment are better than the color markers.3.The Aruco marker obstacle avoidance system for indoor small quadrotor based on Kinect camera is designed and implemented.Tracking and positioning the small quadrotor in the system,and identifying the AR ArUco mark in the space to control the drone to autononously avoid obstacles.