MIT researchers develop robot that can learn to identify objects based on sight and touch

Mail Online | 5/19/2020 | Annie Palmer For
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Robots are getting closer to being able to see and feel the physical world.

A team of researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) developed AI software that's capable of predicting what an object will look like or feel like by using 'sight' and 'touch.'

Study - Humans - Machines - Workplace - Researchers

The study could help humans and machines work together more seamlessly in the workplace, researchers say.

Their findings also bring robots closer to emulating a common function of the human brain: When humans look at an object, they can often anticipate what it will feel like, i.e. hard, soft, flexible, etc.

Humans - Object - Eyes - Picture - Head

Similarly, when humans touch a particular object with their eyes closed, they often form a picture in their head of what they think it looks like.

The team took a KUKA robot arm, a machine often used in warehouses, then outfitted it with GelSight, a type of tactile sensor that's made of rubber and was also developed by a group at MIT.

Researchers - Videos - Objects - Tools - Household

From there, researchers recorded 12,000 videos of 200 objects being touched, including tools, household products and fabrics.

The video clips were broken down into static photos and compiled into a dataset of over 3 million images, called 'VisGel.'

Dataset - Robot - Arm - Relationship - Tactile

After studying this dataset, the robot arm was able to begin learning the relationship between tactile and visual information, with the help of GANs, or general adversarial networks.

GANs essentially operate using two algorithms, one called the generator and the other called the discriminator.

Generator - Judgments - Data - Discriminator

The generator makes judgments based on data, then the discriminator determines whether or not...
(Excerpt) Read more at: Mail Online
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