A simpler method for learning to control a robot
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.
Luca Carlone and Jonathan How of MIT LIDS discuss how future robots might perceive and interact with their environment.
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
Cindy Alejandra Heredia’s journey from Laredo, Texas, took her to leading the MIT autonomous vehicle team and to an MBA from MIT Sloan.
It’s more important than ever for artificial intelligence to estimate how accurately it is explaining data.
A new study finds human supervisors have the potential to reduce barriers to deploying autonomous vehicles.
A new computer vision system turns any shiny object into a camera of sorts, enabling an observer to see around corners or beyond obstructions.
MIT researchers exhibit a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios.
Researchers create a trajectory-planning system that enables drones working together in the same airspace to always choose a safe path forward.
New repair techniques enable microscale robots to recover flight performance after suffering severe damage to the artificial muscles that power their wings.
Robotic parts could be assembled into nimble spider bots for exploring lava tubes or heavy-duty elephant bots for transporting solar panels.
By keeping data fresh, the system could help robots inspect buildings or search disaster zones.
Saverio Cambioni discusses new results revealing the redirected asteroid Dimorphos to be a dust-trailing rubble-pile.
Senior Sylas Horowitz tackles engineering projects with a focus on challenges related to clean energy, climate justice, and sustainable development.