Neural Jacobian Fields, developed by MIT CSAIL researchers, can learn to control any robot from a single camera, without any other sensors.
Robotics
AI shapes autonomous underwater “gliders”
An AI pipeline developed by CSAIL researchers enables unique hydrodynamic designs for bodyboard-sized vehicles that glide underwater and could help scientists gather marine data.
Read MoreDeveloped to analyze new semiconductors, the system could streamline the development of more powerful solar panels.
Read MoreUsing generative AI to help robots jump higher and land safely
MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that out-jumped a robot designed by humans.
Read MorePresentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.
Read MoreAI-enabled control system helps autonomous drones stay on target in uncertain environments
The system automatically learns to adapt to unknown disturbances such as gusting winds.
Read MoreMerging design and computer science in creative ways
MAD Fellow Alexander Htet Kyaw connects humans, machines, and the physical world using AI and augmented reality.
Read MoreNew research could allow a person to correct a robot’s actions in real-time, using the kind of feedback they’d give another human.
Read MoreNew training approach could help AI agents perform better in uncertain conditions
Sometimes, it might be better to train a robot in an environment that’s different from the one where it will be deployed.
Read MoreExpanding robot perception
Associate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.
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