Helping robots handle fluids
Researchers create a new simulation tool for robots to manipulate complex fluids in a step toward helping them more effortlessly assist with daily tasks.
Researchers create a new simulation tool for robots to manipulate complex fluids in a step toward helping them more effortlessly assist with daily tasks.
By mapping the volumes of objects, rather than their surfaces, a new technique could yield solutions to computer graphics problems in animation and CAD.
A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.
SoftZoo is a soft robot co-design platform that can test optimal shapes and sizes for robotic performance in different environments.
Bruce Cameron's research interests include technology strategy, system architecture, and the management of product platforms.
Principal Research Scientist Audun Botterud tackles a range of cross-cutting problems — from energy market interactions to designing batteries — to get closer to a decarbonized power grid.
Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where confidence in the results of a data analysis might break down.
The MIT assistant professor works to get more electricity out of renewable energy systems.
Computational chemists design better ways of discovering and designing materials for energy applications.
John Sterman brings workshops with management flight simulators to businesses working toward environmental sustainability.
New modeling tool enables rapid design of effective and equitable policy combinations.
Analyses show stakeholders of all levels must get involved in decarbonizing pavements to reach climate goals.
A new tool brings the benefits of AI programming to a much broader class of problems.
A method for quickly predicting the forces needed to push objects through "flowable media" could help engineers drive robots or anchor ships.
Comparing models of working memory with real-world data, MIT researchers find information resides not in persistent neural activity, but in the pattern of its connections.