Abstract-This paper presents a novel indoor navigation and ranging strategy by using a monocular camera. The proposed algorithms are integrated with simultaneous localization and mapping (SLAM) with a focus on indoor aerial vehicle applications. We experimentally validate the proposed algorithms by using a fully self-contained micro aerial vehicle (MAV) with on-board image processing and SLAM capabilities. The range measurement strategy is inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals. The navigation strategy assumes an unknown, GPS-denied environment, which is representable via corner-like feature points and straight architectural lines. Experimental results show that the system is only limited by the capabilities of the camera and the availability of good corners.
Celik et al. REF presented a SLAM-based system using a monocular camera and US sensors.
Monocular vision SLAM for indoor aerial vehicles
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
Computer Science