Robotics
Robotics

Robotics

Artificial Intelligence Civil and environmental engineering Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mechanical engineering MIT Schwarzman College of Computing Research Robotics Safety School of Engineering

New control system teaches soft robots the art of staying safe

MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits.

Artificial Intelligence Center for International Studies Classes and programs Collaboration Data Environment Europe Food Global Industry International initiatives Internships machine learning Mechanical engineering MISTI MIT Schwarzman College of Computing MIT Sea Grant Oceanography and ocean engineering Robotics School of Engineering School of Humanities Arts and Social Sciences sensors Software Students UAV Undergraduate Undergraduate Research Opportunities Program (UROP) Water

MIT Sea Grant students explore the intersection of technology and offshore aquaculture in Norway

AquaCulture Shock program, in collaboration with MIT-Scandinavia MISTI, offers international internships for AI and autonomy in aquaculture

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Autonomous vehicles Computer science and technology computer-vision Disaster response Electrical engineering and computer science (EECS) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research Robotics School of Engineering

Teaching robots to map large environments

A new approach developed at MIT could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.

Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Internet machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering Simulation

Using generative AI to diversify virtual training grounds for robots

New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.

Artificial Intelligence Collaboration Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Industry machine learning MIT Schwarzman College of Computing MIT Sloan School of Management President Sally Kornbluth Provost Research Robotics School of Architecture and Planning School of Engineering School of Humanities Arts and Social Sciences School of Science Special events and guest speakers Technology and society

What does the future hold for generative AI?

At the inaugural MIT Generative AI Impact Consortium Symposium, researchers and business leaders discussed potential advancements centered on this powerful technology.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) machine learning Mechanical engineering MIT Schwarzman College of Computing Research Robotics School of Engineering

Robot, know thyself: New vision-based system teaches machines to understand their bodies

Neural Jacobian Fields, developed by MIT CSAIL researchers, can learn to control any robot from a single camera, without any other sensors.

3-D printing Artificial Intelligence Autonomous Underwater Vehicles (AUV) Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Defense Advanced Research Projects Agency (DARPA) Design Electrical engineering and computer science (EECS) Invention machine learning Marine biology MIT Schwarzman College of Computing Research Robotics School of Engineering

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.

Algorithms Artificial Intelligence Computer science and technology computer-vision Department of Energy (DoE) Electrical engineering and computer science (EECS) machine learning Materials science and engineering Mechanical engineering National Science Foundation (NSF) Renewable energy Research Research Laboratory of Electronics Robotics School of Engineering Solar Sustainability

Robotic probe quickly measures key properties of new materials

Developed to analyze new semiconductors, the system could streamline the development of more powerful solar panels.

3-D printing Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Design Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering School of Science

Using 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.

Artificial Intelligence Collaboration Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Faculty Funding Human-computer interaction Industry McGovern Institute Media Lab MIT Schwarzman College of Computing MIT Sloan School of Management Music and theater arts Research Robotics School of Architecture and Planning School of Engineering School of Humanities Arts and Social Sciences School of Science Special events and guest speakers Technology and society

Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.