In order to solve the current stage of agricultural robots in the working channel of the demonstration greenhouse,dynamic obstacle processing is difficult,poor target accessibility,easy to fall into the local minimum and so on, the dual obstacle cost function,adaptive weights and virtual target_ dynamic window approach (DAV_DWA) was proposed to achieve greenhouse robot local path planning. Firstly,a dynamic static dual-strategy obstacle avoidance method was adopted,which divided the safety distance of dynamic and static obstacles into two evaluation functions to reduce the collision risk of dynamic obstacles and prevent excessive obstacle avoidance of static obstacles. Secondly, an adaptive strategy for evaluation function weights was proposed, adaptive adjustment of the weights of each evaluation function according to two obstacle distances to enhance the robot’s path-finding ability in different complex environments. Finally,the virtual goal method was proposed to enable it to continue navigation after detaching from the local minimum,so as to enhance its path planning ability for the local minimum. Comparative simulation experiments and greenhouse experiments were carried out, and the results showed that compared with other algorithms,DAV_DWA was able to reach the target point with a shorter path in a shorter time under the premise of guaranteeing the safety;in the greenhouse scenario,the robot can complete the autonomous navigation task,and the positioning error was no more than 0.12 m, and tracking error was no more than 0.10 m,which was in line with the practical requirements.