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.
AUTOBED
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.
Autonomous Working Smart Machine (AWSM)
POSITION: Mobile Manipulator Robot
COACHES: Yong K. Cho
STATS: Contains multiple manipulators enabling it to assist with human-robot
collaborative tasks that require handling complex objects; uses a dual teleoperated, hand-arm
system to function in hazardous environments as part of a disaster relief team.
HOMETOWN: Robotics and Intelligent Construction Automation Lab (RICAL)
FUN FACT: Boasts 15 degrees of freedom, 19 rotational servos, and three linear
servos.
COZMO
POSITION: Educational Mobile Robot
COACHES: Sonia Chernova, Vivian Chu, Jing Dong, Yang Tian
STATS: Has a variety of sensors that allow it to see people, move objects
(blocks), and navigate in the world; the API allows students to learn how to program robots to
localize and navigate environments and interact with people.
HOMETOWN: Robot Autonomy and Interactive Learning (RAIL)
FUN FACT: Cozmo is used in a class of 250 students and you can find 100 of them
roaming around during lab hours.
DE2BOT
POSITION: Educational Robot
COACHES: Tom Collins, Kevin Johnson
STATS: Using a dedicated FPGA development board, this robot evolves each
semester as students enrolled in the ECE 2031 course add new hardware capabilities or a new
software application.
HOMETOWN: Digital Design Lab
FUN FACT: Used by about 2,500 Georgia Tech undergraduates so far (likely more
than any other robot), DE2BOT introduces robotics novices to the realities of robot perception
and control.
FLORA
POSITION: Experimental Apparatus (Fast, Low-Luminance
Organism-Robot Arena)
COACHES: Simon Sponberg, Steven Chandler, Ravi Chauhan
STATS: As a high-precision positional controlled artificial flower, moths will
feed from the attached sugar water vial, which allows researchers to prescribe a trajectory for
the moth to fly, thus enabling study of the moth's control strategies.
HOMETOWN: Agile Systems Lab
FUN FACT: All electronics and motors must be covered during experiments by a
flexible cloth to protect FLORA from moth poop.
GT-MUR
POSITION: Autonomous Underwater Robot (Georgia Tech
Miniature Underwater Robot)
COACHES: Fumin Zhang, Qiuyang Tao, Sean Maxon
STATS: A small underwater vehicle used dually as a research and educational
platform; GT-MUR is a perfect platform for environmental sampling, human-robot interaction, and
a multi-robot sensing network.
HOMETOWN: Georgia Tech System Research (GTSR)
FUN FACT: This underwater robot is shorter than a foot-long sandwich.
KINGFISHER
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.
BIOROBOTIC EYE
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