Static path planning method of robot

Abstract

The invention relates to a static path planning method of a robot. The method comprises that a target point is set, and an artificial potential field is established within the map range by taking the target point as a terminal point; particle swarm optimization is used, a start point of the robot is provided with m particle swarms, the flight speed of the ith particle in the tth step is vi(t), simulated walking along the path from the start point to the terminal point is carried out on each particle by combining the artificial potential field with the particle swarm optimization, and each particle forms self movement track in the simulated walking process; most particles are converged to one of the multiple tracks gradually, and an optical walking path from the start point to the terminal point is obtained within the map range; and the robot moves from the start point to the terminal point according to the optimal walking path. According to the invention, the potential field method, the grid method and the particle swarm optimization are combined, potential field distribution in a grid map is calculated directly, the pre-planned path is obtained from the target point of the potential field along the direction in which the potential field decreases most rapidly, the method is safe and effective, and path planning is accurate and reliable.

Description

technical field [0001] The invention relates to a static path planning method for a robot, and belongs to the technical field of robot path planning. Background technique [0002] The path planning problem of self-moving robot is one of the core problems in the field of robotics. According to the knowledge of the space environment of the robot, the path planning problem can be divided into static path planning and dynamic path planning. Aiming at the problem of path planning, many algorithms have been proposed, mainly including potential field method, grid method and particle swarm method. Taking the traditional artificial potential field method as an example, it uses a method based on vector synthesis to plan the movement path of the robot under the combined force of the repulsive force from the obstacle and the attractive force from the target point through intuitive rules. . In the case of only local information, its obstacle avoidance strategy is very effective. Howev...

AI Technical Summary

Problems solved by technology

However, since the speed and direction of the robot's movement depend on the magnitude and direction of the force vector sum, when the resultant force is zero, the robot cannot move. This is why the artificial potential field method is easy to fall into a local minimum point.

For the particle swarm optimization algorithm, in the initial stage, the walking paths of the particles are scattered, and the convergence speed of the paths is slow, which affects the efficiency of path planning.

Therefore, different algorithms have their own advantages, but also have their methodological limitations

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