So far, thankfully, we are still beating the robot.
For the uninitiated, Jenga comprises 54 rectangular blocks stacked in 18 layers of three blocks each, with the blocks in each layer oriented perpendicular to the blocks below.
From the data collected, the robot then weighs the possible outcomes of different moves - specifically, whether a block in a certain configuration, and pushed with a certain amount of force, was successfully extracted.
It "learns" whether to remove a specific block in real time, using visual and tactile feedback, in much the same way as a human player would switch blocks if the tower started to wobble. Alberto Rodriguez, the Walter Henry Gale Career Development Assistant Professor in the Department of Mechanical Engineering at MIT, says the robot demonstrates something that's been tricky to attain in previous systems: the ability to quickly learn the best way to carry out a task, not just from visual cues, as it is commonly studied today, but also from tactile, physical interactions.
It also demands mastery of other skills, such as pushing, pulling, probing, placing, and aligning the blocks in the tower. Nima Fazelli and colleagues built a robotic arm gripper that emulates the multisensory action needed to play Jenga, a game in which blocks must be removed from a tower and then placed on top without collapsing the tower.
In a significant breakthrough for robotic manipulation of real-world objects, MIT researchers have created a robot that can play Jenga.
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Researchers say that tasks that need careful physical interaction, such as separating recyclable objects from a landfill and assembling consumer products, could be performed with the system.
The research received support from the US National Science Foundation through the National Robotics Initiative. "As a effect, these systems require far more training data than humans do to learn new models or new tasks, and they generalize much less broadly and less robustly".
In a video, the robot proves that it has actually already mastered the game quite well.
You probably don't give a lot of thought to the physical senses you rely on to probe the blocks in a Jenga tower, but imagine trying to determine the best move by only looking at the tower, it would be toppled at every turn.
During a few informal trials, the robot matched up well against human Jenga players.
"This is the way robotics and AI needs to be moving together", he said, adding that the robot learns by playing in a similar way that a human would.