Researchers at MIT have developed a robot, RF-Grasp, that can sense hidden objects with ‘superhuman perception’.
A research group led by a team at MIT has developed RF-Grasp, a robot that uses penetrative radio frequency to pinpoint items even when they’re hidden from view.
This is because radio waves can pass through walls and sense objects hidden behind them. RF-Grasp uses radio waves alongside more traditional computer vision techniques to locate and grasp such items.
The goal here isn’t to develop an AI that can give you a run for your money in a game of hide and seek. According to associate professor and director of the Signal Kinetics Group at the MIT Media Lab, Fadel Adib, it’s to give robots “superhuman perception”.
A game changer for e-commerce?
Adib is part of a team led by Tara Boroushaki, a research assistant in the Signal Kinetics Group. According to the group, developing robots with superhuman perception could potentially streamline e-commerce fulfilment in warehouses or help machines “pluck a screwdriver from a jumbled toolkit”.
The group explained that warehouse work is still largely carried out by humans despite the fact that working conditions are sometimes dangerous, and one of the reasons is that robots can’t locate and grasp objects in crowded environments.
Another of the researchers, Prof Alberto Rodriguez from MIT’s department of mechanical engineering, said: “Perception and picking are two roadblocks in the industry today. Radio frequency is such a different sensing modality than vision. It would be a mistake not to explore what radio frequency can do.”
Such robots could even have applications in the home, according to Adib, by locating the right Allen wrench while you assemble Ikea furniture. He said: “Or you could imagine the robot finding lost items. It’s like a super-Roomba that goes and retrieves my keys, wherever the heck I put them.”
How RF-Grasp works
Visible light waves cannot pass through walls, which is what stops humans from being able to see through them. RF-Grasp gets around this by using radio waves instead.
Like other radio frequency identification systems, RF-Grasp consists of a reader and a tag. The latter is a tiny computer chip that is attached to the object you want to track. In the case of pets, for example, the chip is implanted.
The reader emits a radio frequency signal that gets modulated by the tag and reflected back to the reader, providing information on the tagged object’s identity and location.
With RF-Grasp specifically, both a camera and a radio frequency reader help it find and grab tagged items. It has a robotic arm with a grasping hand and the camera sits on its wrist. It constantly collects both radio frequency tracking data and a visual picture of its surroundings. It then integrates the two data streams into its decision-making process.
Boroushaki explained: “The robot has to decide, at each point in time, which of these streams is more important to think about. It’s not just eye-hand coordination, it’s radio frequency-eye-hand coordination. So, the problem gets very complicated.”
Adib added: “It starts by using radio frequency to focus the attention of vision. Then you use vision to navigate fine manoeuvres.” He compared it to hearing a siren from behind and looking to get a clearer picture of where it came from.
During testing, RF-Grasp was able to pinpoint and grab target objects with around half as much total movement as its non-radio frequency equivalents. It was also uniquely able to declutter its surroundings, the team said, by removing packing materials and other obstacles to reach the tagged items.