Candiii
[[]]
Year Of Creation	2006-2007
Versions
Current Version	deprecated
Update Year	2007-2008, 2008-2009
Information and Statistics
Farthest Distance	235 feet
Fastest Time	n/a
Highest Placement AutoNav	6th
Highest Placement Design	9th

Competitions

IGVC 2007

Bot Version: Candi
Results
- Distance: 123 feet
- Design Competition Placement: 9th (743 / 1100 points)
- AutoNav Competition Placement: 7th

IGVC 2008

Bot Version: Candii
Results:
- Distance: 185 feet
- Design Competition Placement: 18th (778.33 / 1100 points)
- AutoNav Competition Placement: 9th

IGVC 2009

Bot Version: Candiii
Results:
- Distance: 235 feet
- Design Competition Placement: 21st (476.67 / 1100 points)
- AutoNav Competition Placement: 6th

Versions

Candi (V1.0)

At Competition

Mechanical Issues & Improvements

Old BattleBots motors. A new frame is currently being fabricated from 1" square tubing. New body will have front suspension and a giant ball caster in the rear.

Electrical Issues & Improvements

Router: Motorola WR850GP
- Hardware
  - Broadcom 4712 @ 200MHz
  - Storage: 4MB Flash
  - Ram: 16MB
  - Wireless: Integrated Broadcom
  - Switch: ADM6996L (4 Port)
  - Serial: Two headers
  - Power: +12VDC, 0.5A
- Software
  - OpenWrt (White Russian 0.9)
    - 2.4.30 Kernel
    - Available Software
      - Official Packages
      - 3rd Party Packages
Monitor
Positioning system: IMU 5 Degrees of Freedom
Computer
- Processor: Intel Pentium 4 CPU 2.40GHz
- Physical Memory: 512 MB RAM
- IDE Master
  - 30GB ATA-5 4200RPM HD
  - File system partition = dev/hda2 18GB
Power System
Motor System
Emergency Stop System

Software Issues & Improvements

PlayerStage

Code from Graduate Students - Restricted access (must be logged in to access)

Path Planning Algorithms: Logan proposes that Robojackets consider the use of Support Vector Machine Path Planning as a method of creating an optical set of (x,y) waypoints that Candi may follow in order to dodge obstacles and follow lines. First, check out the wikipedia article on Support Vector Machines to help understand the theory.

Support Vector Machine at Wikipedia

Now, I have posted a paper that explains how this regression method is used in a larger algorithm to find best paths between two data sets. Have a look at it, but skip the first section where they explain the theory (it's the same information as Wikipedia, only a lot less understandable).

File:SVMPP.pdf

As for implementation, we should look at/borrow from/use the SVMlight program - an implementation of SVM in C. Apparently it is quite optimized too (the people who wrote the nice paper used it for experiments). There is a link to it on the Wikipedia page.

Robot Vision:

There are two perspective transforms that need to be implemented, the rectilinearizing transform and the planar perspective transform.

Rectilinearizing Transform
Simple in theory. Very hard to make work fast though. I have posted preliminary MATLAB code and am hoping to use vertex shaders to speed processing and autofill data gaps, but I don't know what hardware is available at the moment or how to write Cg.
Scratch that, I have an OpenGL version working in C so the MATLAB one is unnecessary. Right now the OGL app is stand alone and only works on pictures named "pic.bmp" that are a 720x480 image in the bottom left corner of a 24bit 1024x1024 bmp image. Included is the Cygwin makefile(should work on any system with glut in $INCLUDE but give a warning), the pic.bmp test image, and source. Press any key to quit the program. The source code is massive, so a good text editor will be needed to edit.

Planar Perspective Transform: Version 1.0
Very simple and fast if data given in a convenient format. In development, I will post when I have a semistable implementation.

HOLY SH*T!!!
I went to the railroad today, took a picture with the camera, and dvgrabbed it back home.

I was going to do some math and such, but then I thought, "What the hell, lets see what happens if I just stick it into the transform..." and LOOK WHAT I SAW!:

--->

OGMWTFBBQ&HOW!

I knew it was good, but that is amazing!--Paul 11:32, 20 May 2007 (EDT)