This paper aims to derive advantage of triangle matching method for spacecraft localization by theoretical analysis based on Triangle Similarity Matching (TSM) method, and validates that by the experiment. Concretely, TSM estimates the own location by matching craters in a map of the moon and an image taken by the aircraft. This paper focuses on inner and cross products in the mechanism of TSM, and analyzes that. From the theoretical analysis, we can derive two things: (1) if the only craters outside of the triangles are in the different locations, the inner and the cross products’ values do not relate on the shape; (2) since the inner and the cross products are influenced of the vector’s length, the products should be divided by the length; and (3) the triangles have not to be congruence, but they have to be similar for the advantage of the triangle shape. Furthermore, we improve TSM based on the above findings, and apply it to aircraft localization problems as experiments to validate the effectiveness. From the experimental results, we revealed those things: (a) the modified TSM can perform accurately than any other methods; (b) the modified TSM can decrease the distance from the true location, averagely 0.3, and max 9.52; and (c) the modified TSM can estimate the location in the difficult situations by matching similar triangles.
題目: Analyzing Triangle Matching Method Based on Craters for Spacecraft Localization
著者: Fumito Uwano, Haruyuki Ishii, Yuta Umenai, Kazuma Matsumoto, Takato Tatsumi, Akinori Murata and Keiki Takadama
誌名: Proceedings of the 14th International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS2018)
詳細: Madrid, Spain, June 2017
@inproceedings{fumito uwano 2017analyzing,
title={Analyzing Triangle Matching Method Based on Craters for Spacecraft Localization},
author={Fumito Uwano and Haruyuki Ishii and Yuta Umenai and Kazuma Matsumoto and Takato Tatsumi and Akinori Murata and Keiki Takadama},
booktitle={Proceedings of the 14th International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS2018)},
year={2017},
month={June}
}