Fingertip sensor gives robot unprecedented dexterity

Equipped with a novel optical sensor, a robot grasps a USB plug and inserts it into a USB port.

Researchers at MIT and Northeastern University have equipped a robot with a novel tactile sensor that lets it grasp a USB cable draped freely over a hook and insert it into a USB port.

The sensor is an adaptation of a technology called GelSight, which was developed by the lab of Edward Adelson, the John and Dorothy Wilson Professor of Vision Science at MIT, and first described in 2009. The new sensor isn’t as sensitive as the original GelSight sensor, which could resolve details on the micrometer scale. But it’s smaller — small enough to fit on a robot’s gripper — and its processing algorithm is faster, so it can give the robot feedback in real time.

Industrial robots are capable of remarkable precision when the objects they’re manipulating are perfectly positioned in advance. But according to Robert Platt, an assistant professor of computer science at Northeastern and the research team’s robotics expert, for a robot taking its bearings as it goes, this type of fine-grained manipulation is unprecedented.

“People have been trying to do this for a long time,” Platt says, “and they haven’t succeeded because the sensors they’re using aren’t accurate enough and don’t have enough information to localize the pose of the object that they’re holding.”

The researchers presented their results at the International Conference on Intelligent Robots and Systems this week. The MIT team — which consists of Adelson; first author Rui Li, a PhD student; Wenzhen Yuan, a master’s student; and Mandayam Srinivasan, a senior research scientist in the Department of Mechanical Engineering — designed and built the sensor. Platt’s team at Northeastern, which included Andreas ten Pas and Nathan Roscup, developed the robotic controller and conducted the experiments.

Synesthesia

Whereas most tactile sensors use mechanical measurements to gauge mechanical forces, GelSight uses optics and computer-vision algorithms.

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