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.
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.
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
Read MoreMIT Advanced Vehicle Technology Consortium marks a decade of developing data that improve understanding of how drivers use and respond to increasingly sophisticated automotive features.
Read MoreThe system automatically learns to adapt to unknown disturbances such as gusting winds.
Read More“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.
Read MoreAssociate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.
Read MoreCorvus Robotics, founded by Mohammed Kabir ’21, is using drones that can navigate in GPS-denied environments to expedite inventory management.
Read MoreMIT CSAIL director and EECS professor named a co-recipient of the honor for her robotics research, which has expanded our understanding of what a robot can be.
Read MoreThe MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advance vehicle technology.
Read MoreTesla’s recent innovations in autonomous vehicles and robots present a transformative vision for transportation and work. However, concerns over safety, regulatory oversight, job displacement, and data privacy highlight significant risks. As Tesla advances, the need for effective regulations to protect public interests and ensure responsible use of technology becomes critical.
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