INS integrated motion analysis for autonomous vehicle navigation

Barry A. Roberts; Michael E. Bazakos

doi:10.1117/12.46056

1 May 1991 INS integrated motion analysis for autonomous vehicle navigation

Barry A. Roberts, Michael E. Bazakos

Proceedings Volume 1521, Image Understanding for Aerospace Applications; (1991) https://doi.org/10.1117/12.46056
Event: Munich '91 (Lasers '91), 1991, Munich, Germany

Abstract

This paper presents the results obtained from a maximally passive technique of obstacle detection for ground-based vehicles and rotorcraft. Automatic detection of these obstacles and the necessary guidance and control actions triggered by such detection would facilitate autonomous vehicle navigation. The approach to obstacle detection that is presented in this paper employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to world points within the field of view of the sensor, which can then be used to provide obstacle detection. Many types of existing vehicles contain an inertial navigation system (INS) which can be utilized to greatly improve the performance of motion analysis techniques and make them useful for practical military and civilian applications. Our motion analysis approach makes use of INS data to improve interest point selection, matching of the interest points, and the subsequent motion detection, tracking, and obstacle detection. In this paper we concentrate on the results of our processing when applied to sequences of lab and outdoor imagery. The range measurements that are made by INS integrated motion analysis are compared to a limited amount of ground truth that is available.

Citation Download Citation

Barry A. Roberts and Michael E. Bazakos "INS integrated motion analysis for autonomous vehicle navigation", Proc. SPIE 1521, Image Understanding for Aerospace Applications, (1 May 1991); https://doi.org/10.1117/12.46056

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available