DCTマップ：コサイン変換に基づくコンパクトで微分可能なLiDARマップ
DCT Maps: Compact Differentiable Lidar Maps Based on the Cosine Transform
LiDARマップを位置領域ではなく離散周波数領域で保持し、逆DCTの連続拡張で微分可能な連続スカラー場として復元する手法を提案。グリッドマップより少ないメモリで高精度な表現を実現した。
著者: Alexander Schaefer, Lukas Luft, Wolfram Burgard
分類: cs.CV, cs.RO, eess.IV
原文アブストラクト
Most robot mapping techniques for lidar sensors tessellate the environment into pixels or voxels and assume uniformity of the environment within them. Although intuitive, this representation entails disadvantages: The resulting grid maps exhibit aliasing effects and are not differentiable. In the present paper, we address these drawbacks by introducing a novel mapping technique that does neither rely on tessellation nor on the assumption of piecewise uniformity of the space, without increasing memory requirements. Instead of representing the map in the position domain, we store the map parameters in the discrete frequency domain and leverage the continuous extension of the inverse discrete cosine transform to convert them to a continuously differentiable scalar field in the position domain, which we call DCT map. A DCT map assigns to each point in space a lidar decay rate, which models the local permeability of the space for laser rays. In this way, the map can describe objects of different laser permeabilities, from completely opaque to completely transparent. DCT maps represent lidar measurements significantly more accurate than grid maps, Gaussian process occupancy maps, and Hilbert maps, all with the same memory requirements, as demonstrated in our real-world experiments.
