Towards Consistent State and Covariance Initialization for Monocular SLAM Filters: Utilizing Closed-Form Solutions to Gain Measurement Based and Assumption Free Initial Estimates

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

In this paper we perform a consistency investigation for the initialization of Monocular Simultaneous Localization and Mapping filters by utilizing an existing closed-form solution for metric velocity, landmark distance and attitude determination. This closed-form solution offers a consistent initial estimate for the state as well as the covariance of the considered system. The resulting initialization equations solely rely on monocular images and measurements of an inertial measurement unit (IMU) with 9 degrees of freedom. Furthermore they do not require any prior knowledge or assumptions about the estimates or the surrounding static environment. Based on these analytical expressions, we will derive conditions which are required in order to gain consistent initial estimates. The actual consistency, the accuracy of the initial state and the properties of the initial covariance will then be discussed thoroughly on the basis of simulated experiments.

Details

Original languageEnglish
Pages (from-to)475-489
Number of pages15
JournalJournal of intelligent & robotic systems : with a special section on unmanned systems
Volume80
Issue number3-4
Publication statusPublished - 31 Jan 2015
Peer-reviewedYes

Keywords

Keywords

  • Bearing-only SLAM, Extended Kalman filter, Metric velocity determination, Monocular SLAM, SLAM consistency, SLAM initialization