Research On Path Planning And Obstacle Avoidance Of Quadrotor UAV

In recent years,with the rapid development of the Unmanned Aerial Vehicle(UAV),related technologies have been a hotspot in military reconnaissance,security inspections,agricultural services,and many other fields.The expansion of application scenarios has brought about an exponential increase in environmental information,and the environment faced by UAVs has become increasingly complex.It results in the UAVs requiring higher processing performance,faster execution strategies,and better navigation algorithms.Therefore,there are still certain technical bottlenecks in realizing UAV trajectory planning and autonomous obstacle avoidance.Based on the above reasons,this thesis conducted research on the trajectory planning and obstacle avoidance technology of quadrotor UAVs.It mainly contained three aspects,including UAV spatial positioning technology,3D environment construction,and path planning algorithm improvement,as follows.(1)For this thesis,the quadrotor UAV uses Pixhawk open source hardware to build the hardware system and the PX4,Robot Operating System(ROS)and Mavlink communication protocol are used to form the software debugging platform for the UAV navigation system.Finally,a pinhole camera model of the UAV and a binocular stereo vision model are described.(2)For the needs of 3D spatial localization and environmental map construction of the quadrotor UAV,the GPS,barometer and altitude fixing radar data are filtered using the limiting filter and arithmetic averaging algorithm,the binocular camera and IMU data are fused using the extended Kalman filter algorithm,and the two data are fused in a secondary level with a master-slave weighting strategy,and then the final poses are added to the RTAB-MAP algorithm.Finally,the stability and accuracy of UAV positioning,as well as the effectiveness and feasibility of environmental map construction,were evaluated experimentally.(3)The search step,field of view and crowding factor of the artificial fish swarm algorithm were improved,and the artificial potential field method was fused to introduce the idea of artificial potential field method in the foraging behaviour and random behaviour of the artificial fish swarm to enhance the guidance of the foraging behaviour and random behaviour of the fish swarm and reduce the blind search of the fish swarm.The algorithms before and after the improved fusion are compared using simulation software.The simulation results show that the fused algorithm enters convergence with fewer iterations,shorter convergence time and more efficient algorithm search.(4)A real experimental scenario was built to verify that the UAV could better achieve the UAV surroundings building with the multi-sensor fusion localization and RTAB-MAP algorithm under three different obstacle scenarios,and that the improved artificial fish swarm path planning algorithm could help the quadrotor UAV platform to avoid obstacles and reach the target location smoothly.