As I write this post, one of the greatest sports competitions is taking place on Pebble Beach – The US Masters PGA Golf Tournament. However, as we dig deeper into AI and Robotics, one has to wonder about the longevity events. Chess masters have been belittled for over 20 years since Deep Blue first beat Gary Kasparov in 1997.
Earlier this week, CBS introduced us to the next big thing in golf – LDRIC (Launch Directional Robot Intelligent Circuitry). The robotic sports star’s moniker is — phonetically — in honor of Tiger Woods’s birth name, “Eldrick.” The robot made the hole-in-one on the 16th hole of the Waste Management Phoenix Open in Scottsdale, Arizona, on Wednesday.
LDRIC was developed by Golf Laboratories, a robotics company that develops machines like this one to test out new golf club designs. Pro golfer Gary McCord collaborated with the company on the robot. LDRIC has a pretty powerful swing — it can hit a ball up to 130 mph and can replicate the swing of any golfer out there, its developers say.
“We’re in the age of robots,” Golf Laboratories president Gene Parente said in a video introducing LDRIC. “Golf is an incredibly difficult game and to see it done well and consistently is something that is alluring to the average player and the better player and the beginning player.”
All of that being said, no athlete is perfect. It took LDRIC five tries before it successfully made the hole. Still, it’s better than most human players can say for themselves.
Ultimately, robots do not play sports for fun but push the limits of the possible. Take RoboCup that has been around since Deep Blue’s big win. Sports provide unique physical and artificial intelligence challenges to engineers and scientists trying to build robots that can move and think like people.
“If we can have robots that are advanced enough to play soccer and beat humans, there will be a lot of theory and practical inventions” that go well beyond the playing field, says Andrew B. Williams, a professor of electrical and computer engineering at Marquette University.
At this stage in robot research, practical innovations that seem simple still count as significant leaps forward. Teaching a robot to play soccer on two legs was particularly vexing, says Williams. His students eventually settled on a gait that has its robot bend its legs and lower its center of gravity, providing better balance as it moves forward.
And even the most agile robot can’t play a sport without processing information about what’s happening around it. At RoboCup, robots must be aware of field boundary lines, goals, and other robot players.
“It doesn’t have GPS for the soccer field,” Williams says of his team’s robot. “It can only use markers and information of where it’s been and where it’s at. There are some complex mathematical algorithms that are used for robot localization.” German roboticist Dieter Fox, for instance, is a RoboCup veteran and collaborator of Sebastian Thrun, the Udacity CEO who led Google’s development of a driverless vehicle.
“Through RoboCup,” Williams says, “they developed a lot of the localization algorithms that are used in autonomous driving cars.”
It’s not just soccer helping roboticists innovate. Increasingly, engineers and scientists are using the complex movements and quick processing necessary to play sports to refine robots. But not all sports are so challenging for robots. Some are already beating humans in games we invented. A robotic snake won a race across an Olympic-size swimming pool (below), and a our LDRIC trash talked Rory McIlroy in a golf accuracy contest. There’s also a table-tennis-playing robotic arm and an industrial robot that’s shot jumpers with San Antonio Spur Marco Belinelli.
Soccer, though, is a common language, providing a universal framework familiar to teams from around the world. “Everyone understands soccer,” says Williams, who serves as faculty adviser to a team of Marquette undergraduates who participated in RoboCup 2014 and have qualified for RoboCup 2015.
In a 2010 paper, Claude Sammut of the ARC Centre of Excellence for Autonomous Systems in Australia argued that soccer is uniquely useful in developing robot artificial intelligence “because it requires the robot to perceive its environment, to use its sensors to build a model of that environment and then use that data to reason and take appropriate actions. On a football pitch that environment is rapidly changing and unpredictable, requiring a robot to swiftly perceive, reason, act and interact accordingly.”
Sports aren’t only useful when it comes to developing new robotic systems. They’re also a practical and engaging way to show off what robots can already do. Take this badminton-playing robot built by the Flanders Mechatronics Technology Center in Belgium. As researcher Wim Symens says in the video, “We decided to build a badminton robot to demonstrate new technologies we developed t… [because] it’s a real eye catcher.” To put a finer point on it, robots that play sports get people to pay attention to advancements in robotics.
Now, events like RoboCup are actually part of a weeklong extravaganza of robotic excess with exhibits, symposiums, and workshops, in addition to the robot-on-robot matches. Would it generate the same interest as the Superbowl last week, probably not, but it is perhaps the most popular Robot battle to date, even bigger now than Deep Blue’s victory.