A Global Path Planning Method for Mobile Robots Based on Multiple Improvements of A

Traditional A* algorithm faces challenges in the context of complex environments, optimal solution selection, and non-smooth paths when dealing with the path planning problem for mobile robots. To address these issues, several improvements have been made to the classical A* algorithm, incorporating...

Full description

Saved in:
Bibliographic Details
Main Authors: Chengyu, Liu, Xun, Li, Yiming, Wei, Jinsuo, Wang, Jinguo, Zhou
Format: Conference Proceeding
Language:English
Subjects:
A Algorithm
Bayesian Curve
Heuristic algorithms
Heuristic Function
Mobile Robot
Mobile robots
Path planning
Planning
Runtime
Time factors
Turning
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Traditional A* algorithm faces challenges in the context of complex environments, optimal solution selection, and non-smooth paths when dealing with the path planning problem for mobile robots. To address these issues, several improvements have been made to the classical A* algorithm, incorporating dynamic weighting coefficients, optimizing heuristic functions, and employing Bayesian curve-smoothed paths. These modifications enable the algorithm to achieve favorable search results while considering time constraints. Experimental results demonstrate a significant advantage of the improved algorithm in terms of path length, with a reduction of 1.6 seconds in robot runtime compared to the classical A* algorithm under equivalent conditions, representing a 5% decrease in runtime. Additionally, in local areas with frequent sharp turns and large angles, the robot experiences noticeable speed reduction, effectively avoiding oscillations and potential collisions with walls.
ISSN:1934-1768
DOI:10.23919/CCC63176.2024.10662456