Autonomous
Ground Vehicle Project
Mentor: Dr.
Glen Williams
2005
Undergraduate Summer Research Grants
(USRG)
Texas
A&M University, College Station
TX
May 2005-August 2005
Abstract
The goal of this
project is to construct an autonomous
mobile vehicle for research in
autonomous controls. The guidelines
for the DARPA Grand Challenge contest,
sponsored by DARPA (Defense Advance
Research Project Agents) will be
used as the specification goal
for the vehicle performance. The
contest requires an autonomous
vehicle to travel one hundred and
seventy primarily off-road miles
from Los Angeles to Las Vegas in
ten hours. The autonomous truck
will operate using a software controller
and is equipped with sensors such
as: a SICK Laser Measurement System
(LMS) and a Global Positioning
System (GPS).
I am responsible for writing software that
simulates vehicle dynamics, GPS signal, heading,
and environmental response data that will
be used to test the software controller.
The simulated data will be used in conjunction
with the software controller to ensure a
successful traversal along the designated
route. The simulator imitates digital data
from the SICK LMS and GPS and sends this
data to the controller. The controller then
decide whether to use the brake, throttle
or whether to change the heading of the vehicle
and sends control information back to the
simulator. The simulator generates SICK data
eight times a second and GPS latitude and
longitude twenty times per second.
2004
Research Experience for Undergraduates
(REU)
University
of Kansas, Lawrence KS
Polar
Radar for Ice Sheet Measurements
(PRISM)
Intelligent
Systems Team, Mentor: Dr. Prasad
Gogineni
May
2004-August 2004
Abstract
Scientists
have speculated that due to long-term
global climate change there is a
surplus of water being released from
polar ice sheets. Although there
is much speculation, they have insufficient
data to prove this theory. This uncertainty
has prompted scientist to explorer
the interactions between ice sheets,
oceans, and atmosphere in an attempt
to quantify the role of ice sheets
in sea level rise. Scientists and
engineers at the University of Kansas
are applying their expertise to develop
and utilize innovative radar and
robotic rovers to measure ice thickness
and determine bedrock conditions
below the ice sheets in Greenland
and Antarctica. This combination
of data will help earth scientists
determine how quickly the polar ice
sheets are melting and to make more
accurate predictions of the effects
of this melting on sea level rise.
The Polar Radar for Ice Sheet Measurements (PRISM) project aims to design and develop an autonomous mobile radar system to measure polar ice sheets. The PRISM team is divided into four primary areas: Communication, Robotics, Intelligent Systems, and Radar. The Communication team is creating technologies that enable communication with the rover, in the field, and also from the field to the University of Kansas. The Robotics group created a virtual prototype model that has been a guide to the design and operation of the rover, which includes maneuverability limits, speed limits and antenna towering capability. The Radar team produced radar systems that are required to execute the scientific measurement of the ice sheets, and the Intelligent Systems team has designed the specification for an intelligent agency for radar and vehicle control.
We are currently working with the Intelligent Systems team using the PRISM Intelligent System codebase to get an understanding of the issues involved in the design and implementation of multi-agent systems. Agents share some common properties but are also very diverse. Some agents are mobile while others are static, some communicate through messages others don’t communicate at all, and some perform task individually while others work cooperatively. The study of multi-agent systems focuses on systems in which many intelligent agents interact with each other. Using the PRISM codebase, we are enhancing our understanding of multi-agent systems and contributing to the PRISM project by creating UML models of key parts of the multi-agent architecture including the MatchMaker, and the underlying RMI system that allows agents to communicate with other agents over networks. Using UML we will develop a class diagram of a messaging subsystem and also a sequence diagram of an agent getting data from a sensor.
Using UML I have developed a sequence diagram of a temperature agent getting data from a remote temperature sensor. The diagram illustrates the various objects and methods that are used when the temperature agent talks to the temperature sensor on the robotic rover. With this model the Prism Intelligent Systems Team can plan modifications and additions to the multi-agent system. The diagram will help plan for additional functionality for next years field test.