US engineers develop language-learning robot

The group, led by associate professor Jeffrey Mark Siskind, has developed three algorithms that allow a wheeled robot to learn the meanings of words, to use words to generate a sentence, and to comprehend sentences.

The team took a small-wheeled robot outfitted with several cameras and ran numerous trials on an enclosed course containing several objects such as a chair, a traffic cone and a table.

Sentences describing the path for the robot to take were provided by anonymous online sources. An operator then steered the robot to follow the paths described by the sentences.

Using the algorithms, the robot was able to recognise words associated with objects within the course and words associated with directions of travel based on its sensory data.

“It was able to generate its own sentences to describe the paths it had taken. It was also able to generate its own sentences to describe a separate path of travel on the same course,” said Siskind. “The robot aggregated its sensory data over numerous experiences.”