Machine path planning method and mobile robot

Abstract

The invention provides a machine path planning method and a mobile robot. The method comprises the following steps: searching a to-be-processed region on an original grid map, and corroding the to-be-processed area to obtain a first map; processing the first map in a first preprocessing mode to obtain a second map which comprises a skeleton path diagram; finally determining the current position and the final position of a machine, and obtaining a planned path in combination with a first search rule and the skeleton path diagram. According to the technical scheme of the invention, an obstacle area on an original grid map is subjected to corrosion, and the skeleton path diagram of the map is extracted according to the first search rule, and the planned path is obtained by combining the firstsearch rule with the skeleton path diagram; the mobile robot is enabled to avoid obstacles during walking through the optimization software algorithm, the walking safety of the mobile robot is improved, the map established by the mobile robot is more stable, and the user experience is improved.

Description

technical field [0001] The invention relates to the field of robots, in particular to a machine path planning method and a mobile robot. Background technique [0002] Mobile robots are widely used in many fields such as industrial production, life services, and environmental detection. Among them, path planning is the key research direction of many skilled in the art. The existing technology usually uses the A star algorithm on the basis of grid maps However, when the map is large, it will cause the A star algorithm to perform very frequent sorting operations on arrays or linked lists with increasing scale when searching for paths, resulting in increased calculations and longer time required for path planning . In addition, when there are many obstacles in the map, the path planned by the A star algorithm will make the distance between the robot and the obstacles too small, making the robot less safe when walking, and may even be trapped by traps. Therefore, it is necessary...

AI Technical Summary

Problems solved by technology

[0002] Mobile robots are widely used in many fields such as industrial production, life services, and environmental detection. Among them, path planning is the key research direction of many skilled in the art. The existing technology usually uses the A star algorithm on the basis of grid maps However, when the map is large, it will cause the A-star algorithm to perform very frequent sorting operations on arrays or linked lists with increasing scale when searching for paths, resulting in increased calculations and longer time required for path planning

In addition, when there are many obstacles in the map, the path planned by the A star algorithm will make the distance between the robot and the obstacles too small, making the robot less safe when walking, and may even be trapped by traps. Therefore, it is necessary to Robots make improvements

Images