Primary Goals• Fully develop vision system for

Wunderbot IV autonomous robot• Adapt it specifically for June 2008

Intelligent Ground Vehicle Competition (IGVC)

Secondary Goals• Code a closed-loop motor control

system for accurate robot motion response

• Writing/debugging of LabVIEW code for synchronization of all hardware subsystems

Vision System – Prior Work• Acquisition of DVT Legend 554C XE

high-resolution video camera• Coding of LabVIEW sub-VI to acquire

camera’s TCP/IP communication string

Vision System - Tasks1) Build camera mount at optimal location

and angle2) Image processing to parse white lines in

robot’s vision3) Manage line data in LabVIEW and

integrate with adaptable motion-control algorithms to steer robot on correct path

4) Properly format the gathered vision data to interface with path-planning code – will be used to map traversed course

Status - Fall 2007• Primitive path detection algorithm

calculated gradient• Found high contrast in two small,

filtered regions to simulate stereo vision

1. Camera Mount• Built as part of new utility pole, sits

back 16” from rear bumper and 4’ up• Secured with adjustable wing nuts on

angle brackets

Viewable Region

Processing Time Reduction• Increase of viewable region allows

cropping of imageTop Edge Cropped

Processing Time Speedup

15% (153 lines) 16% (90ms)

24% (246 lines) 25% (140ms)

2. Image Processinga) 3x3 dilate filterb) Hough Transform for line detectionc) Line thickness sensor

i. 75% intensity contrastii. Accepts first 3 chains of 50 pixels

(possibly 3 best, but much slower)

Image Processing SamplesUnfiltered Filtered

arbitrary results

more accurate

Image Processing SamplesUnfiltered Filtered

useless data accurate

Preliminary Results

Filtering Shadowsa) Maximum separation of 300 pixels

(window width of 1079)b) “Straightness” of less than 75-pixel

deviation from averaged center line

accepted

filtered

3. Motor Control• Line position data sent to on-board

PC via TCP/IP• LabVIEW code plots the line on a

local (soon global) map

• Line depth and lateral position determine how sharply to turn and whether to back up

Far

Near(sharper turn)

Immediate Obstacle(sharper

turn)

Outlying Obstacle

Outlying Obstacle

• Designed controls for adjusting numerous parameters - allow dynamic motor control adaptation for different environments− Overall target speed− Backup speed− Proximity for backing up− Turning aggressiveness (factoring depth

and lateral position separately)− Minimum line width

• Control panel

Video Clip (2x speed, 23 sec.)

Upcoming Tasks• Introduce line averaging, where

points outside a given standard deviation are discarded

• Increase rate of TCP/IP data transfers• Integrate all subsystems and plot

global, dynamic map of lines and obstacles

References• R. Bishop. LabVIEW 8 Student Edition, Book & CD-ROM Edition,

Upper Saddle River, NJ: Prentice Hall, 2006.• Installation and User Guide for DVT Vision Sensors, Cognex

Corporation, May 2006.• DVT Script Reference Manual, Cognex Corporation, August

2003.• Dougherty, Edward R. Electronic imaging technology,

Bellingham, WA: SPIE Optical Engineering Press, 1999.• A.L. Kesidis and N. Papamarkos. “A Window-Based Inverse

Hough Transform.” Pattern Recognition 33 (2000): 1105-1117.