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.