News Archives - Page 9 of 27 - Robotics Institute Carnegie Mellon University

Transparent, Reflective Objects Now Within Grasp of Robots

Carnegie Mellon Researchers Teach Robots To Infer Shapes From Color Images   PITTSBURGH—Kitchen robots are a popular vision of the future, but if a robot of today tries to grasp a kitchen staple such as a clear measuring cup or a shiny knife, it likely won't be able to. Transparent and reflective objects are the [...]

Bonatti Receives Microsoft Research Dissertation Grant

Rogerio Bonatti, a Ph.D. candidate in the Robotics Institute, is one of 10 recipients across North America who will receive Microsoft Research Dissertation Grants to support research for their Ph.D. thesis. Bonatti, who expects to complete his dissertation next year, has focused his research at the intersection of machine learning theory and motion planning. His [...]

Three Robotics Institute Students Awarded National Science Foundation Fellowships

Robotics Institute PhD students, Keene Chin, Victoria Dean and Jason Zhang, are amongst the 2020 National Science Foundation's Graduate Research Fellowship Program Recipients. The NSF GRFP recognizes and supports outstanding graduate students in NSF-supported STEM disciplines who are pursuing research-based master's and doctoral degrees. Keene Chin, Victoria Dean and Jason Zhang Keene Chin is [...]

Kaess Wins Inaugural RSS Test of Time Award

Carnegie Mellon University Associate Research Professor Michael Kaess poses for a portrait with an autonomous submersible robot in the High Bay of Newell Simon Hall on October 22, 2018. Michael Kaess, associate research professor in the Robotics Institute, and Frank Dellaert, a Ph.D. alumnus of the School of Computer Science and a professor [...]

A New Approach to Lunar Robots

            NASA's MoonRanger robot will rely on fully autonomous operations during its week-long mission, a level of autonomy that has never been achieved before in such a manner on the moon, says Red Whittaker of the Carnegie Mellon Robotics Institute - RI.   By Kimberly Underwood The current development of [...]

Analysis of Complex Geometric Models Made Simple

Monte Carlo Method Dispenses With Troublesome Meshes   Carnegie Mellon University researchers have shown complex shapes need not be divided into intricate meshes, left, to perform geometric analysis. Instead of spending 14 hours creating a mesh, they use Monte Carlo methods to get initial results in less than a minute of the amount of [...]

CMU Method Makes More Data Available for Training Self-Driving Cars

Additional Data Boosts Accuracy of Tracking Other Cars, Pedestrians PITTSBURGH—For safety's sake, a self-driving car must accurately track the movement of pedestrians, bicycles and other vehicles around it. Training those tracking systems may now be more effective thanks to a new method developed at Carnegie Mellon University. Generally speaking, the more road and traffic data [...]