To achieve path planning for dual-robot collaboration in forestry robotics, this paper uses visual imaging principles and image processing methods to locate and segment tree images. Then, a kinematic model of the forestry robot is constructed and solved. The Shoal Optimization Algorithm (SHO) and Informed-RRT* algorithm are combined to propose the SHOInformed- RRT* algorithm for path planning in dual-robot collaboration in forestry robotics. Through simulation experiments, it is found that compared with other methods, the proposed SHO-Informed-RRT* algorithm performs best in terms of path planning time, planning speed, path length, average number of sampling points, and number of path nodes. After adopting the SHO-Informed-RRT* algorithm, the mechanical arm of the forestry robot achieves the optimal set target, and the average movement time of the mechanical arm is the shortest.