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Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are aiming to develop robots that can both maneuver around on land and take to the skies. In a new paper, the team presented a system of eight quadcopter drones that can fly and drive through a city-like setting with parking spots, no-fly zones, and landing ...
7 nov. 2023 · Part of Robotics@MIT and Embodied Intelligence@MIT. We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots. Our goal is to create robots that can perform the kinds of everyday tasks that come naturally to humans, but that are beyond the reach of current technology.
A novel system developed at MIT uses RFID tags to help robots home in on moving objects with unprecedented speed and accuracy. The system could enable greater collaboration and precision by robots working on packaging and assembly, and by swarms of drones carrying out search-and-rescue missions.
18 janv. 2023 · It’s time for Atlas to pick up a new set of skills and get hands on. In this video, the humanoid robot manipulates the world around it: Atlas interacts with ...
Kismet (robot) Kismet now resides at the MIT Museum. Kismet is a robot head which was made in the 1990s at Massachusetts Institute of Technology ( MIT) by Dr. Cynthia Breazeal as an experiment in affective computing; a machine that can recognize and simulate emotions. The name Kismet comes from a Turkish word meaning "fate" or sometimes "luck".
Searching for principles. In 2009, Kim accepted an assistant professorship in MIT’s Department of Mechanical Engineering, where he established his Biomimetic Robotics Lab and set a specific research goal: to design and build a four-legged, cheetah-inspired robot. “We chose the cheetah because it was the fastest of all land animals, so we ...
27 févr. 2024 · For instance, in a warehouse with 800 robots, decongesting a group of 40 robots requires holding the other 760 robots as constraints. Other approaches require reasoning about all 800 robots once per group in each iteration. Instead, the researchers’ approach only requires reasoning about the 800 robots once across all groups in each iteration.
