학술논문

Global Path Planning of UGVs in Large-Scale Off-Road Environment Based on Improved A-star Algorithm and Quadratic Programming
Document Type
Conference
Source
2023 IEEE Intelligent Vehicles Symposium (IV) Intelligent Vehicles Symposium (IV), 2023 IEEE. :1-7 Jun, 2023
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Uncertainty
Intelligent vehicles
Path planning
Real-time systems
Safety
Quadratic programming
Path Planning
Off-road Environment
A* Algorithm
Quadratic Programming
Efficiency Improvement
Language
ISSN
2642-7214
Abstract
Global path planning is an essential component of intelligent vehicle study. This paper designs a two-layer global path planning method based on an improved A* algorithm and quadratic programming for UGVs in a large-scale off-road environment. In the first layer, we generate a global path from the current node to the target node via an improved A* algorithm, with a grid map containing the information of non-accessible areas and uncertainty of off-road terrains as input. The second layer smooths the entire path based on quadratic programming. We adopt efficiency improvement methods in both layers, which ensure the real-time performance of the algorithm. The planner has been verified by simulation and experiments, and the results validate the practicability and real-time performance of the designed method.