Director: Dr. Larry D. Pyeatt (pyeatt@cs.ttu.edu)


From left to right: Todd Quasny, Julian Hooker, Ajay Bansal, Sriram Sundararajan, Srividya Kona, Larry Pyeatt, and Stacy Swinburn. (Picture from Jan. 2001)


Would you like to see more pictures from the lab? Take a look at our Photo Albums!


Current Research Projects:


Obstacle Avoidance for a Mobile Robot Mobile robots continually suffer from obstacles, both stationary and moving. We attempt to provide a robust architecture for avoiding such obstacles given the minimal amount of information about the environment itself and relatively inaccurate and unreliable sensing devices.
Water Recovery System Automation Project The Water Recovery System Automation Project is a collaborative effort between the Civil Engineering (CE) Department and the Computer Science (CS) Department at Texas Tech University. The goal of the project is to extend the existing water recovery system (WRS), developed in the CE department as a joint venture with NASA's Johnson Space Center (JSC) and Texas Tech University (TTU), with an artificially intelligent control system developed by the CS department.
Autonomous Vehicles Actively Touring Academic Regions (AVATAR) Outdoor robotics pose several grand challenges in the area of mobile robotics. To encapsulate these issues into a single problem, a campus tour guide robot is being developed.
Learning Sub-cognitive Behaviors The behaviors that humans perform are quite often either completely reflexive or were learned at an early age and have since become reflexive in nature. Higher level behaviors are ordered sets of these sub-cognitive behaviors. We are developing solutions for learning these low-level, sub-cognitive, behaviors in order to provide them to intelligent agents for ordering in high-level behaviors.
Robot Mapping and Navigation Robot Navigation is at the very heart of the lab. Problems to solve under this group include occupancy grids for mapping, Monte Carlo localization, and Markov localization.
Decision Tree Function Approximation Decision Tree function approximation shows much promise in many areas of AI including reinforcement learning.
Partial Observability in Computation Processing information that is partially observable is an important aspect of many AI applications.


Lab Equipment:
ALBERT (Autonomous Large Beowulf for Exploring Rough Terrain) Large robot for research in outdoor mapping and navigation. Under construction.
simon Nomadics SuperScout II mobile robot for research in indoor mapping and navigation.
Johnny SRI Small Vision System on pan/tilt head. Can be mounted on either robot.
Thing Eshed Robotec Scorbot ER-VII robotic manipulator.
dijkstra Sun Ultra 60, 2 CPU's, 1 Gb RAM, Creator 3D graphics,SUNPCI
norvig Sun Ultra 10, 256 Mb RAM
bellman Sun Ultra 10, 256 Mb RAM
turing Sun Ultra 10, 256 Mb RAM, SUNPCI
markov Sun Ultra 5, 256 Mb RAM
satriani Sun Ultra 5, 256 Mb RAM
nebula Sun Ultra 5, 256 Mb RAM
earth Sun Ultra 1, 128 Mb RAM
magoo Dual Pentium III 500 Mhz Running RedHat Linux, 512Mb RAM (for vision system)
other Construction and test equipment: oscilliscope, digital analyzer, soldering iron, etc.

Current Research Group Members: Past research group members:
Todd Quasny
Last modified: Mon Oct 27 15:08:41 CST 2003