A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
Students learn about the complexity behind simple, everyday movement before experimenting with mechanical models.
Researchers develop an algorithm that decides when a “student” machine should follow its teacher, and when it should learn on its own.
The MIT Sailing Pavilion, the oldest collegiate organization of its kind, offers community members a chance to sail for free — or just enjoy the good vibes.
SoftZoo is a soft robot co-design platform that can test optimal shapes and sizes for robotic performance in different environments.
Rather than start from scratch after a failed attempt, the pick-and-place robot adapts in the moment to get a better hold.
The three-fingered robotic gripper can “feel” with great sensitivity along the full length of each finger – not just at the tips.
“DribbleBot” can maneuver a soccer ball on landscapes such as sand, gravel, mud, and snow, using reinforcement learning to adapt to varying ball dynamics.
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.