| Abstrakt: |
In order to make the auxiliary training ball picking robot pick up the ball efficiently, the path planning of the ball picking robot is needed. The traditional A-star algorithm can be applied to project the trajectory of the mobile robot under the motion model, but there are problems of general obstacle avoidance and insufficient accuracy of obstacle avoidance, based on the characteristics of iteration of the colony algorithm to improve the accuracy of the algorithm. This paper proposes an approach to make the A* algorithm iterative to improve the ability of the algorithm to perform path planning. Compared with the separate A* and colony algorithms, the algorithm in this paper is more accurate and efficient in handling complex routes. It is also paired with object recognition and grasping functions to achieve the function of identifying basketballs, grasping them and transporting them back to the players for the ball pickup robot. In the final Matlab simulation experiments, the effectiveness of target recognition, object grasping, and optimized path recognition is verified. Among them, the optimization algorithm of A* shortens the length of the path by 28% after 40 iterations. [ABSTRACT FROM AUTHOR] |
