Safe Path Planning Based on Anytime Dynamic A-Star Algorithm for Mobile Robots in Indoor Environment

In recent years, considerable concern has arisen about the broad applications of autonomous mobile robots. However, little research has been done on safe routes in the field of route planning for robotic control systems. Safe paths are tracking that reserve robot size for the generated solution in advance to prevent colliding walls and obstacles in the real-time application. Therefore, this article aims to design a safe path algorithm to solve some motion planning problems that might occur in the moving process of mobile robots. This study proposed two different path planning approaches, the safe AD-star and improved AD-star algorithms, which involved novel search and extraction mechanisms combining the MASK technique. The result of this study showed that the improved AD-star algorithm reduced the search nodes, danger factors, and execution time on PC and Embedded Platform Computer (EPC) by 66.9%, 91.1%, 46.4%, and 54.5%, respectively, compared to the traditional AD-star algorithm. Compared to the safe AD-star algorithm, the improved AD-star algorithm decreased the search nodes and execution time on PC and EPC by 68.8%, 81.0%, and 85.6%, respectively. In conclusion, this investigation proved competitive with the existing state-of-the-art. It successfully demonstrated efficacy for the application of mobile robots in the field of path planning and provided latecomers with a better understanding of safe path planning.