Efficiency-optimized path planning algorithm for car-like mobile robots in bilateral constraint corridor environments

In the field of mobile robot path planning, optimizing mobility efficiency is paramount for enhancing operational productivity. This paper presents a novel path planning algorithm designed to optimize mobility efficiency. The algorithm generates free paths and employs turning points for segmentation, while Dubins and clothoid curves are utilized for path smoothing within kinematic constraints. An evaluation function, considering dynamic variables like velocity loss and distance traveled during turning, selects the optimal path for mobility efficiency. Experimental results reveal that the shortest path in length is not always the most efficient. Comparative analysis with the Hybrid A* algorithm showcases the proposed algorithm's ability to generate smooth paths across various constraint environments, thereby enhancing robot mobility. Validation experiments on a custom-developed three-wheeled mobile robot confirm the effectiveness of the derived paths. This efficiency-optimized path planning algorithm finds practical application in settings such as factories with dual-boundary constraints and intricate corner configurations, offering time-saving trajectories to bolster overall robot operational efficacy.