Simultaneous localisation and mapping problems in indoor environments with stereovision

Abstract

This paper proposes a method for simultaneous localisation and mapping (SLAM) in an indoor environment using stereo vision. Specially designed artificial landmarks distributed in the environment are observed and extracted from a camera image. The disparity map obtained from the stereo vision system is used to obtain the ranges to these landmarks. The main contribution of the paper is the formulation of the mathematical framework for SLAM for a robot moving on a planar surface among landmarks distributed in three dimensional space. The paper also presents the results of experiments conducted using a Pioneer robot and a Triclops stereo vision system. It is demonstrated that accurate robot and feature locations can be obtained using the proposed technique.

A computationally efficient EKF-vSLAM

“…Solving the SLAM problem with vision as the only external sensor is now the goal of much of the effort in the area. Monocular vision is especially interesting as it offers a highly affordable solution in hardware terms [3], [4], [5], [6] and [7]. The common problem with all implementation of vSLAM (single-camera, Stereo-Vision) is the state vector size and the full covariance matrix, which in large environments may become prohibitively large and causes substantial computational problems.…”