人工智能
计算机视觉
计算机科学
同时定位和映射
初始化
机器人学
单眼
特征(语言学)
弹道
智能摄像头
移动机器人
机器人
语言学
物理
哲学
程序设计语言
天文
作者
Andrew J. Davison,Ian Reid,Nicholas Molton,Olivier Stasse
标识
DOI:10.1109/tpami.2007.1049
摘要
We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to Structure from Motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live augmented reality with a hand-held camera.
科研通智能强力驱动
Strongly Powered by AbleSci AI