SLAM using camera and IMU sensors.

Abstract

Visual simultaneous localization and mapping (VSLAM) is the problem of using video input to reconstruct the 3D world and the path of the camera in an 'on-line' manner. Since the data is processed in real time, one does not have access to all of the data at once. (Contrast this with structure from motion (SFM), which is usually formulated as an 'off-line' process on all the data seen, and is not time dependent.) A VSLAM solution is useful for mobile robot navigation or as an assistant for humans exploring an unknown environment. This report documents the design and implementation of a VSLAM system that consists of a small inertial measurement unit (IMU) and camera. The approach is based on a modified Extended Kalman Filter. This research was performed under a Laboratory Directed Research and Development (LDRD) effort.