Abstract
This paper proposes a risk map generation method that considers the occupied space of objects and their characteristics. The objective is to guide visually impaired individuals safely to their intended destinations using a guide dog robot that can assist them in walking. The number of guide dogs in active service in Japan has been continuously declining, which has prompted the development of guide dog robots. The robot utilized in this study employs Mecanum wheels, the RoboSense RS-LiDAR-16 sensor, and Intel’s RealSense Depth Camera D435 to scan the surrounding environment and measure distance up to 150 m. To prevent visually impaired individuals from entering spaces potentially occupied by objects, the three-dimensional spatial information of the objects is projected onto a two-dimensional map, and object recognition is performed to project the potential risks of objects onto the map. The generated risk map is used to path planning that considers the risk levels established according to object properties. The effectiveness is proven by experiments of guiding visually impaired individuals to destinations while avoiding potential occupied spaces.
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Aoki, T., Zhang, B., Lim, Ho. (2024). 3D Spatial Information Reflected 2D Mapping for a Guide Dog Robot. In: Li, J., Zhang, B., Ying, Y. (eds) 6GN for Future Wireless Networks. 6GN 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 553. Springer, Cham. https://doi.org/10.1007/978-3-031-53401-0_1
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DOI: https://doi.org/10.1007/978-3-031-53401-0_1
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