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@article{179099,
        author = {R Harinandan and Mahesh Kumar N and Deepak G and Manasa R},
        title = {A Comparative Review on Visual Docking Guidance Systems: Technologies, Advancements, and Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5952-5963},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179099},
        abstract = {Visual Docking Guidance Systems (VDGS) play a crucial role in ensuring safe and efficient aircraft docking at airport stands, leveraging advanced sensing and computational technologies. This review provides a comprehensive analysis of recent advancements in VDGS, including infrared laser, 3D scanning, LiDAR, machine learning, and computer vision-based docking methodologies. The study examines the integration of radar data simulation, automated VDGS message interpretation, and hybrid sensing approaches, such as TriDAR, to enhance docking precision. Additionally, we explore the applications of vision-based guidance in underwater docking, spacecraft rendezvous, and autonomous vehicle docking, highlighting the cross- domain adaptability of these technologies. The paper discusses control strategies such as Non-Linear Model Predictive Control (NMPC) and Control Barrier Functions (CBFs) for safe autonomous docking manoeuvres. Finally, key challenges, including environmental limitations, real-time data processing constraints, and safety concerns, are addressed along with potential research directions for future developments in VDGS. This review aims to serve as a foundational reference for researchers and industry professionals working on docking automation and intelligent guidance systems.},
        keywords = {Visual Docking, Computer Vision, Machine Learning, Augmented Reality, Sensor Fusion, Autonomous Systems, Aviation, 5G, Edge Computing.},
        month = {May},
        }