Autonomous navigation with constrained consistency for C-Ranger

Zhang, S., He, B., Ying, L., Li, M. and Yuan, G. (2016) Autonomous navigation with constrained consistency for C-Ranger. International Journal of Advanced Robotic Systems, 11(6), 84.

Abstract

Autonomous underwater vehicles (AUVs) have become the most widely used tools for undertaking complex exploration tasks in marine environments. Their synthetic ability to carry out localization autonomously and build an environmental map concurrently, in other words, simultaneous localization and mapping (SLAM), are considered to be pivotal requirements for AUVs to have truly autonomous navigation. However, the consistency problem of the SLAM system has been greatly ignored during the past decades. In this paper, a consistency constrained extended Kalman filter (EKF) SLAM algorithm, applying the idea of local consistency, is proposed and applied to the autonomous navigation of the C-Ranger AUV, which is developed as our experimental platform. The concept of local consistency (LC) is introduced after an explicit theoretical derivation of the EKF-SLAM system. Then, we present a locally consistency-constrained EKF-SLAM design, LC-EKF, in which the landmark estimates used for linearization are fixed at the beginning of each local time period, rather than evaluated at the latest landmark estimates. Finally, our proposed LC-EKF algorithm is experimentally verified, both in simulations and sea trials. The experimental results show that the LC-EKF performs well with regard to consistency, accuracy and computational efficiency.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Li, Dr David
• Authors: Zhang, S., He, B., Ying, L., Li, M., and Yuan, G.
• Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
• College/School: College of Science and Engineering > School of Engineering
• Journal Name: International Journal of Advanced Robotic Systems
• Publisher: IN-TECH
• ISSN: 1729-8806
• ISSN (Online): 1729-8814
• Published Online: 06 June 2016
• Copyright Holders: Copyright © 2016 The Authors
• First Published: First published in International Journal of Advanced Robotic Systems 11(6):84
• Publisher Policy: Reproduced under a Creative Commons License