協調測位のための検出・フィルタリングフレームワーク
A Detection and Filtering Framework for Collaborative Localization
高精度センサを持つ先導車に追従するADAS車両の測位精度を、視覚とオドメトリの姿勢情報をフィルタリングで統合して改善する手法を提案した。
著者: Thirumalaesh Ashokkumar, Katherine A Skinner, Siddarth Agarwal, Ankit Vora, Ashutosh Bhown
分類: cs.RO
原文アブストラクト
Increasingly, autonomous vehicles (AVs) are becoming a reality, such as the Advanced Driver Assistance Systems (ADAS) in vehicles that assist drivers in driving and parking functions with vehicles today. The localization problem for AVs relies primarily on multiple sensors, including cameras, LiDARs, and radars. Manufacturing, installing, calibrating, and maintaining these sensors can be very expensive, thereby increasing the overall cost of AVs. This research explores the means to improve localization on vehicles belonging to the ADAS category in a platooning context, where an ADAS vehicle follows a lead "Smart" AV equipped with a highly accurate sensor suite. We propose and produce results by using a filtering framework to combine pose information derived from vision and odometry to improve the localization of the ADAS vehicle that follows the smart vehicle.
