不確実な動的環境のための3Dレーダー速度マップ
3D Radar Velocity Maps for Uncertain Dynamic Environments
空間座標を高次元特徴空間に射影しベイズ線形回帰で3D速度マップを推定、不確実性も定量化する手法を提案し、空中・地上データセットで有効性と拡張性を示した。
著者: Ransalu Senanayake, Kyle Beltran Hatch, Jason Zheng, Mykel J. Kochenderfer
分類: cs.RO, cs.CV
原文アブストラクト
Future urban transportation concepts include a mixture of ground and air vehicles with varying degrees of autonomy in a congested environment. In such dynamic environments, occupancy maps alone are not sufficient for safe path planning. Safe and efficient transportation requires reasoning about the 3D flow of traffic and properly modeling uncertainty. Several different approaches can be taken for developing 3D velocity maps. This paper explores a Bayesian approach that captures our uncertainty in the map given training data. The approach involves projecting spatial coordinates into a high-dimensional feature space and then applying Bayesian linear regression to make predictions and quantify uncertainty in our estimates. On a collection of air and ground datasets, we demonstrate that this approach is effective and more scalable than several alternative approaches.
