Batch gating for data association in monocular SLAM

Abstract

This work describes the development and implementation of a single-camera SLAM system, introducing a novel data validation algorithm. A 6-DOF monocular SLAM method developed is based on the Delayed Inverse-Depth (DI-D) Feature Initialization, with the addition of a new data association batch validation technique, the Highest Order Hypothesis Compatibility Test, HOHCT. The DI-D initializes new features in the system defining single hypothesis for the initial depth of features by stochastic triangulation. The HOHCT is based on evaluation of statistically compatible hypotheses, and search algorithm designed to exploit the Delayed Inverse-Depth technique characteristics. Experiments with real data are presented in order to validate the performance of the system.