AI News, Georgia Tech robots learn to ‘MacGyver’ simple tools

Georgia Tech robots learn to ‘MacGyver’ simple tools

Thanks to new technology that enables them to create simple tools, robots may be on the verge of their own version of the Stone Age.

Using a novel capability to reason about shape, function, and attachment of unrelated parts, researchers have for the first time successfully trained an intelligent agent to create basic tools by combining objects.

The breakthrough comes from Georgia Tech’s Robot Autonomy and Interactive Learning (RAIL) research lab and is a significant step toward enabling intelligent agents to devise more advanced tools that could prove useful in hazardous – and potentially life-threatening – environments.

Using machine learning, the robot is trained to match form to function – which object shapes facilitate a particular outcome – from numerous examples of everyday objects.

“We want to reach that level of reasoning in our work, which is something we’re working on now.” The inspiration for the work comes from the popular story of Apollo 13, the doomed seventh crewed flight of the Apollo space program.

“We want to make robots that can assist humans in these kinds of scenarios to take the pressure off of them to come up with innovative solutions and potentially save their lives.” This work was presented at the 2019 Robotics: Science and Systems conference in a paper titled “Autonomous Tool Construction Using Part Shape and Attachment Prediction”

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