Creating and verifying stable AI-controlled systems in a rigorous and flexible way
Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
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Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
This technique could lead to safer autonomous vehicles, more efficient AR/VR headsets, or faster warehouse robots.
By enabling models to see the world more like humans do, the work could help improve driver safety and shed light on human behavior.
Autonomous helicopters made by Rotor Technologies, a startup led by MIT PhDs, take the human out of risky commercial missions.
The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.
Jonathan How and his team at the Aerospace Controls Laboratory develop planning algorithms that allow autonomous vehicles to navigate dynamic environments without colliding.
Researchers from MIT and Stanford University have devised a new machine-learning approach that could be used to control a robot, such as a drone or autonomous vehicle, more effectively and…
Walking to a friend’s house or browsing the aisles of a grocery store might feel like simple tasks, but they in fact require sophisticated capabilities. That's because humans are able…
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.