Global smooth path planning method for mobile robot

Abstract

The invention relates to a global smooth path planning method for a mobile robot. The method includes the following steps: carrying out environmental modeling according to the working environment of the mobile robot; establishing an objective function to be optimized according to the principle of safe and shortest path; carrying out path planning of the mobile robot based on an adaptive particle swarm algorithm; outputting a motion path of the mobile robot according to an optimization result; and smoothing the motion path of the mobile robot by adopting Bezier curves. According to the method,the adaptive particle swarm algorithm is combined with the Bezier curves, so that the stability and robustness are strong, the search efficiency can be effectively improved, the path length can be shortened, and the intention of manual planning is met; and moreover, the method has few parameters to be adjusted, is simple in model, and is suitable for global smooth path planning of multiple mobilerobots in complex environments.

Description

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AI Technical Summary

Benefits of technology

The present invention provides a path planning method for mobile robots in complex environments. The method divides the working area into small squares and assigns numbers to each square, making it easier to represent and visualize the path points. The method also uses an adaptively adjusted particle swarm algorithm to plan the robot's path, improving search accuracy and efficiency. Additionally, the method uses Bezier curves to smooth the path, resulting in a shorter and smoother trajectory. Overall, this method is suitable for planning smooth paths for various mobile robots in complex environments.

Problems solved by technology

This patented describes different techniques or approaches related to improving the accuracy and effectiveness of navigating mobile robotic systems (MARV). However, current solutions may require significant resources and slow down operations when trying to plan paths with complicated objects like walls or corners. Therefore, an improvement would provide more efficient ways to navigate through challenging environments without sacrificing precision.

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