Study On Reliability Of Data Link And Path Planning Of Agricultural Quad-rotor UAV

Agricultural Mini-UAV is playing a greater role in precision agriculture. It has become a new hot spot in agricultural machinery industry.The reliability of the agricultural Mini-UAV data link is the key factor that affects its stability. In order to improve and test the reliability of the agricultural Mini-UAV data link, we designed the redundancy switching system of radio modem and the quality testing system of radio communication in this paper. We study the path-planning algorithm for quad-rotor UAV, which works in the complex agricultural environment in the hilly ground. It mainly includes on-line estimation of wind field in agricultural environment and flight path planning algorithm in wind field. The calculation of wind field is based on the information from sensors on UAV.The main contents are as follows:1. The redundancy switching system of radio modem is designed, based on the data link platform constructed by 3DR and QGroundControl of PX4. It includes the selection of relay and radio and the design of hardware circuit and so on.2. The quality testing system of radio communication is designed. It includes the design of the source of interference, software programming and the implementation of testing environment. Then the reliability of the data link is tested. The test result shows that the redundancy switching system of radio modem can effectively improve the reliability of data link.3. The on-line estimation of the wind field in the complex agricultural operation environment is studied. The wind field has a great influence on the track of Mini-UAV. In order to find the optimal flight trajectory of the Mini-UAV, it is necessary to estimate the wind field.4. The path planning algorithms for agricultural quad-rotor UAV based on wind field estimation are studied. Firstly, we design a path-planning algorithm, which ignored the information of wind field. Sencondly, in order to design two different kinds of on-line route planning methods, we construct different fitness functions and corresponding optimization strategies. The two methods are named ant colony algorithm-one and ant colony algorithm-two, respectively. Finally, the three algorithms are simulated and analyzed under different wind fields. The simulation results show that the path planning by the ant colony algorithm-two is the optimal path of the three algorithms.