Robot path planning method integrating artificial potential field and logarithm ant colony algorithm

Abstract

The invention provides a robot path planning method integrating an artificial potential field and a logarithm ant colony algorithm. The method comprises the following steps: S1, initializing; S2, establishing a grid map containing obstacle information; S3, establishing a movable grid table of the ants according to the current positions of the ants; S4, calculating an attractive force and a repulsive force received by the position of the current ant in the artificial potential field, establishing an influence function q (t) of the artificial potential field, and calculating a minimum included angle between a resultant force borne by the ant in the artificial potential field and an adjacent grid direction; S5, improving an ant colony algorithm heuristic function eta ij and a pheromone updating strategy; S6, calculating the transition probability density of the improved ant colony algorithm, and updating the tabu table; S7, judging whether path planning exploration is completed or not, ifnot, entering S3, and if yes, entering S8; and S8, performing re-iteration or ending according to the judgment condition. According to the method, the convergence speed of the ant colony algorithm inpath planning is effectively improved, and the situation that the artificial potential field algorithm is prone to falling into local optimum is reduced to a great extent.

Description

technical field [0001] The invention belongs to the technical field of robot path planning, and relates to a robot path planning method integrating artificial potential field and logarithmic ant colony algorithm. Background technique [0002] Path planning refers to searching for a collision-free optimal or suboptimal path connecting the starting pose and the target pose of the mobile robot in a complex and changeable obstacle environment according to a specific path evaluation index. Path planning is one of the key technologies of autonomous mobile robot navigation, and it is a hotspot and difficulty in mobile robot research. It is closely connected with mobile robot motion control, map construction, robot positioning, etc. Ant colony algorithm is a typical global path planning algorithm. Since the path planning of the ant colony algorithm is a process of advancing while exploring, the calculation of the path planning algorithm is complex and slow. Liu Changan et al. prop...

AI Technical Summary

Problems solved by technology

But this method will increase the shortest path of the robot and become time-consuming

Li Lina and others proposed a firefly algorithm combined with an artificial potential field algorithm, using the artificial potential field method as an initialization guide factor to initialize the parameters of the firefly algorithm to speed up the initial search time of the algorithm, but this algorithm introduces too many nodes , making the operation of the whole algorithm complicated and wasting too much time

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