An Improved A* Based Path Planning and Control Strategy for Autonomous Sanitation Vehicles in Campus Environments

Abstract

To address the problems of "missed operation tasks, high risk of path scraping, and low search efficiency" in the path planning of autonomous sanitation vehicles in smart parks, this paper proposes an optimization scheme based on an improved A* algorithm and Bézier curve. Based on the traditional A* algorithm, the neighborhood expansion is optimized to reduce invalid traversal, and redundant nodes are pruned through the "collinearity judgment + safe distance verification" strategy. A cubic Bézier curve is introduced to smooth the polyline path, adapting to the kinematic constraints of sanitation vehicles. Experimental results show that the number of traversed nodes of the improved A* algorithm is reduced, with significantly improved path safety and real-time performance guaranteed. The Bézier curve achieves continuous curvature, solving the problem of sudden steering. The proposed path planning scheme balances the requirements of operation completeness, kinematic safety, and planning efficiency, providing technical support for the intellectualization of environmental maintenance in smart parks.