Research And Implementation Of Vision-based Indoor Autonomous Navigation System For Quadrotor

The micro-UAV has the advantages of light and portable,it can replace human to detect the unknown environment and accomplish some complex and dangerous tasks,which can reduce the risk of casualties.In recent years,UAV with the function of autonomous exploration in unknown environment is a new wave of research on military and civilian drones.Based on this background,this paper focuses on the technologies of real-time positioning,reconstruction of environment and path planning,then we make up a micro-UAV platform for indoor autonomous navigation.First of all,this paper completes the visual odometer based on RGB-D camera,includes using pinhole camera model,and using ORB algorithm for the feature points of adjacent key frames extracting and matching,and the initial inter-frame pose estimation is realized by EPnP algorithm.Secondly,the extended Kalman filter(EKF)is used to loosely couple the visual odometer data and IMU data to solve the camera pose estimation error easily when camera moves fast and rotates purely.Then this paper derives the extended Kalman prediction model and the observation model though the formula,and on this basis realizes the visual-inertial odometer.And then the global and local pose maps are constructed by the back-end optimization,and the BA algorithm is used to get the posture trajectory and map for a long time.Furthermore,according to the accumulated errors in the process of large-scale camera movement,the BoW algorithm is used to complete loop detection.And according to the needs of the scene,four environmental maps for different purposes are generated.Finally,the visual SLAM algorithm is completed,and the improved RRT~* algorithm is used to realize path planning in Octomap map.Before physical debugging,the hardware-in-the-loop simulation of the system is carried out under gazebo,which guarantees the stability and function of all the algorithms as well as the four-rotor platform of the system and reduces the risk of crashing.In the simulation,the SLAM algorithm,RRT~* algorithm and the stability of the whole system are validated.In the end,the micro quadrotor hardware platform was built,consists of a ASUS RGB-D camera,a Intel NUC processor and a Pixhawk flight control.And then,the attitude stability,SLAM algorithm real-time and path planning test were carried out indoors.The experimental results show that the micro quadrotor system have good performance of timeliness,dynamic and robustness in indoor positioning,three-dimensional perception of the environment,map building and path planning.