Robotic Mouse Makes Maze Debut at UC San Diego

submitted by: ucsandiego
An intrepid group of University of California, San Diego undergraduates has designed and build a robotic mouse from scratch. The electrical engineering and computer science undergraduates from the Jacobs School of Engineering also wrote the software to teach the robot to solve a maze. The team unveiled their mouse at the IEEE Region 6 Southwest Area Spring Meeting on Saturday, April 25th, held at UC San Diego.

Robot Design for 2009 IEEE Micromouse Competition by ALex Forencich and Jeffrey Wurzbach

submitted by: CharlesTu

EUReKA 2009: Robot Design for 2009 IEEE Micromouse Competition

San Diego Science Festival -- Nifty Fifty -- Dr. Javier Movellan

submitted by: sdscienccefestival

Dr. Javier Movellan speaks to students of Sacred Heart Middle School about machine intelligence.

Talk by Lim

submitted by: dougramsey

Lecturer Lim leads a discussion on the Science of Learning Centers sponsored by the National Science Foundation, what they do, what are their purpose and goals, and how they are implemented in assisting a new generation of individuals expand their education and build on it.

MX-2 Space Suit Analogue

submitted by: eternes

University of Maryland undergraduates Ali Husain, Heather Bradshaw and Adam Mirvis make a splash with their research on the spacesuit of tomorrow in the University of Maryland 's Neutral Buoyancy Research Facility .

Dual axis moment exchange inverted pendulum

submitted by: graham.gabe

Hardware demonstration and explanation of an inverted pendulum, stabilized by two independently controlled reaction wheels connected to DC motors. Made as part of a master's thesis at the System and Identification and Control Laboratory at the University of California, San Diego.

Robust source-seeking hybrid controllers for nonholonomic vehicles (experiment)

submitted by: mayhew

This video shows an experiment involving a mobile robot, an IR-camera vision system, and a wireless network. The robot queries the vision system for position information. The robot uses this position information to simulate a potential function in its environment. The hybrid controller uses these measurements in a coordination of vehicle steering and an optimization algorithm to drive the vehicle to the minimum of the function (shown as a blue 'x').