Simultaneous Localization and Mapping of a Mobile Robot with Surveillance and Flying Cameras

Localization and exploration of robotic systems has been a highly active research area in recent years. In order to explore unknown environments with better precision, a robotic system employing surveillance and flying cameras is proposed in this paper. Specifically, a mobile robot equipped with an onboard monocular camera performs visual simultaneous localization and mapping with extended Kalman filtering (EKF-VSLAM) and moves from indoor to outdoor environments. To correct the estimation errors of the system during the task, a least squares-based correction approach is proposed. The proposed robotic system employs surveillance cameras in indoor environment and a flying camera in outdoor environment to correct estimation error from the onboard monocular camera. The proposed correction approach, integrated with the conventional EKF-VSLAM, has been validated by experiments demonstrating better precision.