Path planning for mobile robots in greenhouse orchards based on improved A* and fuzzy DWA algorithms

In complex greenhouse orchard environments, reasonable path planning algorithms are crucial for ensuring efficient and high-quality operation of mobile robots. The unstructured layouts of greenhouse orchard environments, which feature many irregular obstacles, pose high demands on navigation accuracy. Ideal path planning algorithms need to plan a safe and efficient navigation path in complex environments. In this paper, we propose a path planning fusion algorithm which integrates improved A* algorithm and Fuzzy Dynamic Window Approach (FDWA) algorithm. Firstly, the A* algorithm that introduces the rate of environmental obstacles is designed for generating global paths in greenhouses. The search strategy can be changed according to the number of environmental obstacles. Then, a rule to optimize the search neighborhood is proposed to adjust the search neighborhood to five-neighborhood, which improves the node search efficiency. Further, a local path planning strategy incorporating fuzzy control is proposed to enable the robot to maintain a safe distance from obstacles and improve the stability of obstacle avoidance. Finally, the effectiveness of proposed algorithm is verified via the simulated environment and actual greenhouse, respectively. The simulation results show that, the improved A* algorithm reduces the critical turning points and total steering angle by a maximum of 40%. The actual greenhouse experimental results show that, in three different paths, the proposed fusion algorithm reduces the distance deviation by a maximum of 31.8% and the heading angle deviation by a maximum of 28.6%, while increasing the safety distance by up to 30%.