Autonomous vehicles
Autonomous vehicles

Autonomous vehicles

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.

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Eco-driving measures could significantly reduce vehicle emissions

New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.

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Celebrating an academic-industry collaboration to advance vehicle technology

MIT Advanced Vehicle Technology Consortium marks a decade of developing data that improve understanding of how drivers use and respond to increasingly sophisticated automotive features.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Autonomous vehicles Computer science and technology Drones Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research Robotics School of Engineering

AI-enabled control system helps autonomous drones stay on target in uncertain environments

The system automatically learns to adapt to unknown disturbances such as gusting winds.

Algorithms Artificial Intelligence Autonomous vehicles Civil and environmental engineering Computer science and technology Data Emissions IDSS Laboratory for Information and Decision Systems (LIDS) Logistics machine learning MIT Schwarzman College of Computing Research School of Engineering Sustainability Traffic management Transportation

New tool evaluates progress in reinforcement learning

“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.

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Expanding robot perception

Associate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.

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Startup’s autonomous drones precisely track warehouse inventories

Corvus Robotics, founded by Mohammed Kabir ’21, is using drones that can navigate in GPS-denied environments to expedite inventory management.

Algorithms Artificial Intelligence Autonomous vehicles Awards, honors and fellowships Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Faculty Human-computer interaction MIT Schwarzman College of Computing Robotics School of Engineering

Daniela Rus wins John Scott Award

MIT 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.

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Building an understanding of how drivers interact with emerging vehicle technologies

The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advance vehicle technology.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Autonomous vehicles computer-vision Disaster response Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory machine learning MIT Schwarzman College of Computing Natural disasters Research Robotics School of Engineering

Helping robots zero in on the objects that matter

A new method called Clio enables robots to quickly map a scene and identify the items they need to complete a given set of tasks.