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@article{176448,
        author = {Nishant Bhandigare and Siddhesh Jondhale and Sanket Patil},
        title = {Automated Crater Detection and Obstacle Pathfinding for Lunar Rover Navigation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {8035-8043},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176448},
        abstract = {This study presents an innovative approach to lunar surface exploration by developing automated systems for crater detection and safe rover navigation. The project uses advanced artificial intelligence (AI) and machine learning (ML) techniques to address the challenge of detecting craters and boulders from high-resolution Orbiter High Resolution Camera (OHRC) images. It also incorporates a pathfinding algorithm to ensure obstacle-free navigation for lunar rovers in challenging terrains, particularly the Moon’s south pole. The proposed method improves the efficiency and accuracy of lunar exploration and facilitates scientific research and mission planning.
By enhancing both the accuracy and speed of navigation processes, this approach facilitates obstacle-free routes, optimizing rover performance and supporting scientific re- search and mission planning. The integration of automated systems for crater detection and navigation not only paves the way for safer lunar exploration but also contributes to our understanding of the Moon’s geological features.
Through experiments and simulations, this research aims to demonstrate the feasibility of the proposed technologies, setting a foundation for future lunar missions that require autonomous navigation capabilities. As the exploration of space advances, our project stands to impact the next generation of rovers capable of conducting long- duration missions on the lunar surface.},
        keywords = {},
        month = {May},
        }