In order to address the challenges of high labour intensity, low efficiency and harsh working environment in Chinese duck egg collecting operations, this study proposes an optimization technique for egg-collecting robot path planning based on ROS (Robot Operating System). Firstly, the Gmapping algorithm is used to map the laboratory environment for navigation purposes, while the AMCL (Adaptive Monte Carlo Localization) method is used to obtain the pose information of the egg-collecting robot. Secondly，the sequence of egg collecting tasks is determined using the ACA （Ant Colony Algorithm） to compute the shortest path length and node order. Finally， the navigation target points for egg collecting are computed to obtain their world coordinate positions. The global path planning for egg collecting is performed using the Dijkstra algorithm, and the local path planning and obstacle avoidance for the robot is implemented using the DWA (Dynamic Window Approach) algorithm. A test platform was set up based on the actual working environment of the egg-collecting robot to conduct continuous egg collecting navigation experiments, and the final egg collecting navigation accuracy rate was 89.3%.