Improved A* Algorithm for Intelligent Navigation Path Planning

For path planning in intelligent navigation, traditional navigation maps currently fail to meet the requirements of autonomous navigation and optimal path search in terms of three-dimensional environmental features and accuracy. Therefore, the study combined multiple sensors of LIDAR and depth camera to construct a three-dimensional simulation environment map model, and the optimized A* algorithm used to improve path planning. The cost proportion factor and improved heuristic function were used to optimize the A* algorithm. Through experimental comparison before and after optimization, the shortest path and time of the A* algorithm in the 8×8 grid map before optimization were 12.89 and 0.56s, respectively. It had a shortest path and time of 28.76 and 0.28s in a grid map of 16×16, respectively. The improved A* algorithm had an optimal path and time of 12.26 and 0.34s on an 8×8 grid map, and a shortest path and time of 26.34 and 0.28s on a 16×16 grid map. These experiments confirm that the improved A* algorithm improves the search range and efficiency of path planning. This demonstrates its superiority for intelligent navigation path planning and provides technical references for environmental map construction and optimal path planning. © 2024 Slovene Society Informatika. All rights reserved.