Major League Machines
Since 2013, Georgia Tech's Institute for Robotics and Intelligent Machines (IRIM) has annually released a set of trading cards to celebrate National Robotics Week. These fun cards highlight some of Tech’s most talented and productive researchers.
In 2014, IRIM teamed up with IEEE Spectrum and iRobot to create a second set of their popular robot cards. Each year they produce a new national deck featuring famous robots developed by companies and researchers in the U.S. And don't forget about IEEE Spectrum’s award-winning, internationally acclaimed Robots for iPad app, which you can get for FREE on iTunes.
See the Georgia Tech 2017 cards below. Click cards to enlarge.
POSITION: Assistive Robot
COACHES: Charlie Kemp, Henry Evans, Phillip M. Grice, Yash Chitalia, Megan Rich, Henry M. Clever, Ari Kapusta
STATS: A robotic bed that can sense and reposition a person's body; more than two years of use in the home of a person with severe quadriplegia
HOMETOWN: The Healthcare Robotics Lab
FUN FACT: Collaborates with other robots to provide assistance; Invacare is working to commercialize part of Autobed.
POSITION: Environment Monitoring Robot
COACHES: Cédric Pradalier, Shane Griffith
STATS: Autonomously surveys and monitors changes in shore appearance over long duration using collected images; used for ecosystem monitoring, infrastructure state evaluation, and research on perception for natural environments.
HOMETOWN: DREAM Lab at Georgia Tech-Lorraine
FUN FACT: Collected more than six million images over 120 km of autonomous operation since 2013.
LEAF PICKING ROBOT
POSITION: Agricultural Robot
COACHES: Gary McMurray, Konrad Ahlin, Ai-Ping Hu, Nader Sadegh
STATS: Uses machine learning to recognize healthy and unhealthy leaves in a peanut field; the robot then uses visual servoing to approach the leaf and grasp it.
HOMETOWN: Food Processing Technology Lab
FUN FACT: The robot will be installed on a tractor in the summer of 2017 to work in a Georgia peanut field.
Robotically Augmented Electric Guitar (RAEG)
POSITION: Musical Robot
COACHES: Gil Weinberg, Takumi Ogata
STATS: Allows musician to perform on fret-board while robotic components excite and dampen the string; a human performer and robotic mechanisms produce sounds jointly.
HOMETOWN: Robotic Musicianship Lab
FUN FACT: This guitar can already perform complex rhythmic patterns that its creator wouldn't be able to play.
POSITION: Bio-inspired Robot
COACHES: Jun Ueda, Joshua Schultz, Michael Kim
STATS: The fast-moving robotic eye reproduces saccades and smooth-pursuit like ocular movements in coordination with dynamics-based image processing methods.
HOMETOWN: Biorobotics and Human Modeling Lab
FUN FACT: It can move as quickly as the human eye