Novel obstacle-avoiding path planning for crop protection UAV using optimized Dubins curve

In recent years, the crop protection unmanned aerial vehicle (UAV) has been raised great attention around the world due to the advantages of more efficient operation and lower requirement of special landing airport. However, there are few researches on obstacle-avoiding path planning for crop protection UAV. In this study, an improved Dubins curve algorithm was proposed for path planning with multiple obstacle constraints. First, according to the flight parameters of UAV and the types of obstacles in the field, the obstacle circle model and the small obstacle model were established. Second, after selecting the appropriate Dubins curve to generate the obstacle-avoiding path for multiple obstacles, the genetic algorithm (GA) was used to search the optimal obstacle-avoiding path. Third, for turning in the path planning, a strategy considering the size of the spray width and the UAV’s minimum turning radius was presented, which could decrease the speed change times. The results showed that the proposed algorithm can decrease the area of overlap and skip to 205.1%, while the path length increased by only 1.6% in comparison with the traditional Dubins obstacle-avoiding algorithm under the same conditions. With the increase of obstacle radius, the area of overlap and skip reduced effectively with no significant increase in path length. Therefore, the algorithm can efficiently improve the validity of path planning with multiple obstacle constraints and ensure the safety of flight.