仮想テンプレート合成とマッチングによる火星サンプルリターンのためのローバ自己位置推定
Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching
数年前に別ローバが撮影した参照画像からメッシュを構築し、その部分レンダリングを現在のローバ画像と照合することで、荒涼とした地形や大きな照明・視点変化に頑健な視覚的自己位置推定手法を提案した。
著者: Tu-Hoa Pham, William Seto, Shreyansh Daftry, Barry Ridge, Johanna Hansen, Tristan Thrush, Mark Van der Merwe, Gerard Maggiolino, Alexander Brinkman, John Mayo, Yang Cheng, Curtis Padgett, Eric Kulczycki, Renaud Detry
分類: cs.RO, cs.CV
原文アブストラクト
We consider the problem of rover relocalization in the context of the notional Mars Sample Return campaign. In this campaign, a rover (R1) needs to be capable of autonomously navigating and localizing itself within an area of approximately 50 x 50 m using reference images collected years earlier by another rover (R0). We propose a visual localizer that exhibits robustness to the relatively barren terrain that we expect to find in relevant areas, and to large lighting and viewpoint differences between R0 and R1. The localizer synthesizes partial renderings of a mesh built from reference R0 images and matches those to R1 images. We evaluate our method on a dataset totaling 2160 images covering the range of expected environmental conditions (terrain, lighting, approach angle). Experimental results show the effectiveness of our approach. This work informs the Mars Sample Return campaign on the choice of a site where Perseverance (R0) will place a set of sample tubes for future retrieval by another rover (R1).
