Abstract: Obstacle avoidance motion planning is an important direction in the research of intelligent fruit picking. Its goal is to find the optimal path for the robot arm to avoid obstacles in real time in the complex and changeable unstructured orchard environment. This paper introduces several optimization algorithms for obstacle avoidance motion planning according to the time sequence proposed by related optimization algorithms, including A* algorithm based on graph-searching, artificial potential field algorithm based on optimization theory, ant colony algorithm, and fast random tree search algorithms and deep reinforcement learning algorithms; This paper focuses on the principles of several algorithms and their applications in robot obstacle avoidance motion planning, compared the advantages and disadvantages of various algorithms, and carries out the development trend of picking robot obstacle avoidance motion planning algorithms.