Abstract
This paper describes an off-line (i.e. pre-navigation) methodology for machines/robots to identify zebra crossings and their respective orientations within pedestrian environments, for the purpose of identifying street crossing ability. Not knowing crossing ability beforehand can prevent path trajectories from being accurately planned pre-navigation. As such, we propose a methodology that sources information from internet 2D maps to identify the locations of pedestrian street crossings. This information is comprised of road networks and satellite imagery of street intersections, from which the locations/orientations of zebra-pattern crossings can be identified by means of trained neural networks and proposed verification algorithms. The methodology demonstrated good capability in detecting and mapping street crossings’ locations, while also showing good results in verifying them against falsely detected objects in satellite imagery. Orientation estimation of zebra-pattern crossings, using a proposed line-scanning algorithm, was found to be within an error range of 4\(^{\circ }\) on a limited test set.
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Notes
- 1.
Further description of an OSM file’s structure can be found in [9].
- 2.
Using the resolution of an image, the aerial zoom level and the GPS center (i.e., the GPS location of a given street intersection), estimation of the GPS bounds is achievable by means of Mercator projection calculations [18].
- 3.
The urban location on which the test was conducted is a random area within the Shinjuku ward in Tokyo, Japan. This area is bound between the GPS coordinates (i.e. latitude and longitude) of [35.6994726204,139.718178435] and [35.6975273796,139.716821565].
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Acknowledgements
This study was supported by Waseda University Grant for Special Research Projects Number 2018A-047. The study was also partially supported by Waseda University-Graduate Program for Embodiment Informatics Research Grant. For both grants, we wish to express our sincere gratitude.
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Farid, A., Matsumaru, T. (2021). Pre-robotic Navigation Identification of Pedestrian Crossings and Their Orientations. In: Ishigami, G., Yoshida, K. (eds) Field and Service Robotics. Springer Proceedings in Advanced Robotics, vol 16. Springer, Singapore. https://doi.org/10.1007/978-981-15-9460-1_6
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