Abstract: This paper proposed an improved greedy strategy suitable for robot sorting path planning to solve the problem of the traditional sequential path planning algorithm being inefficient. For the small robotic arm system， the logistics palletizing system was comprehensively reconstructed，and the sorting path of the logistics palletizing was planned by the greedy algorithm，significantly reducing the path completion time. Considering that the greedy algorithm may fall into the local optimal situation in the path planning process， this paper designed a probability density function to improve the greedy algorithm and enhance the practicability of the algorithm. The feasibility of the algorithm was verified by building the palletizing robot. The experiment results showed that the improved greedy sorting path algorithm was significantly lower than the traditional sequential scheduling algorithm in terms of total time，and the operating efficiency of the robotic arm increased by 20% - 28% on average，which verified the effectiveness of the improved greedy algorithm in palletizing and sorting path planning.

Key words: path planning, sequential algorithm, greedy strategies, logistics palletizing system, probability density function