Share Email Print

Proceedings Paper

Combining a modified vector field histogram algorithm and real-time image processing for unknown environment navigation
Author(s): Kumud Nepal; Adam Fine; Nabil Imam; David Pietrocola; Neil Robertson; David J. Ahlgren
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Q is an unmanned ground vehicle designed to compete in the Autonomous and Navigation Challenges of the AUVSI Intelligent Ground Vehicle Competition (IGVC). Built on a base platform of a modified PerMobil Trax off-road wheel chair frame, and running off a Dell Inspiron D820 laptop with an Intel t7400 Core 2 Duo Processor, Q gathers information from a SICK laser range finder (LRF), video cameras, differential GPS, and digital compass to localize its behavior and map out its navigational path. This behavior is handled by intelligent closed loop speed control and robust sensor data processing algorithms. In the Autonomous challenge, data taken from two IEEE 1394 cameras and the LRF are integrated and plotted on a custom-defined occupancy grid and converted into a histogram which is analyzed for openings between obstacles. The image processing algorithm consists of a series of steps involving plane extraction, normalizing of the image histogram for an effective dynamic thresholding, texture and morphological analysis and particle filtering to allow optimum operation at varying ambient conditions. In the Navigation Challenge, a modified Vector Field Histogram (VFH) algorithm is combined with an auto-regressive path planning model for obstacle avoidance and better localization. Also, Q features the Joint Architecture for Unmanned Systems (JAUS) Level 3 compliance. All algorithms are developed and implemented using National Instruments (NI) hardware and LabVIEW software. The paper will focus on explaining the various algorithms that make up Q's intelligence and the different ways and modes of their implementation.

Paper Details

Date Published: 19 January 2009
PDF: 8 pages
Proc. SPIE 7252, Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques, 72520G (19 January 2009); doi: 10.1117/12.807650
Show Author Affiliations
Kumud Nepal, Trinity College (United States)
Adam Fine, Trinity College (United States)
Nabil Imam, Trinity College (United States)
David Pietrocola, Trinity College (United States)
Neil Robertson, Trinity College (United States)
David J. Ahlgren, Trinity College (United States)

Published in SPIE Proceedings Vol. 7252:
Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?