Carnegie Mellon University (CMU)

Carnegie Mellon University (CMU) Articles

Displaying 1 - 14 of 14
20th December 2018
Collaboration focuses on next-generation machine learning

It has been announced by Honeywell that they are entering a strategic collaboration with Carnegie Mellon University to advance robotics technology for distribution centres. The initiative brings together Honeywell Intelligrated, a division of Honeywell Safety and Productivity Solutions, and Carnegie Mellon’s National Robotics Engineering Center in Pittsburgh, Pennsylvania.

3D Printing
25th April 2018
Inexpensive 3D printer can produce self-folding materials

Researchers at Carnegie Mellon University have used an inexpensive 3D printer to produce flat plastic items that, when heated, fold themselves into predetermined shapes, such as a rose, a boat or even a bunny. Lining Yao, assistant professor in the Human-Computer Interaction Institute and director of the Morphing Matter Lab, said these self-folding plastic objects represent a first step toward products such as flat-pack furniture that assume...

3D Printing
17th April 2018
3-DIY: printing your own bioprinter

  Researchers at Carnegie Mellon University have developed a low-cost 3D bioprinter by modifying a standard desktop 3D printer, and they have released the breakthrough designs as open source so that anyone can build their own system.

Test & Measurement
11th December 2017
EEG system achieves highest signal resolution

Carnegie Mellon University engineers and cognitive neuroscientists have demonstrated that a new high-density EEG can capture the brain’s neural activity at a higher spatial resolution than ever before. This next generation brain-interface technology is the first non-invasive, high-resolution system of its kind, providing higher density and coverage than any existing system. It has the potential to revolutionise future clinical and neur...

17th August 2017
Sensors and AI: the dream team

You don’t have to attach sensors to everything. With machine learning, a new suite of only nine different sensors can recognise dozens of various phenomena. Ubiquitous sensors seem almost synonymous with the Internet of Things (IoT), but some Carnegie Mellon University researchers say ubiquitous sensing - with a single, general purpose sensor for each room - may be better. Author: Hermann Straubinger

7th July 2017
Real-time detector reads body language

Researchers at Carnegie Mellon University's Robotics Institute have enabled a computer to understand the body poses and movements of multiple people from video in real time — including, for the first time, the pose of each individual's fingers. The method was developed with the help of the Panoptic Studio, a two-story dome embedded with 500 video cameras. The insights gained from experiments in that facility now make it possible to det...

23rd June 2017
Exoskeletons incorporate direct feedback from the body

Researchers at the College of Engineering at Carnegie Mellon University have developed a novel design approach for exoskeletons and prosthetic limbs that incorporates direct feedback from the human body. The findings were published in Science. This technique, called human-in-the-loop optimisation, customises walking assistance for individuals and significantly improves energy economy during walking. The algorithm that enables this optim...

12th September 2016
DoC: latest paradigm for big data computing

Diana Marculescu and Radu Marculescu have been awarded an NSF grant to develop a paradigm for Big Data computing. Specifically, this project focuses on a Datacenter-on-a-Chip (DoC) design consisting of thousands of cores that can run compute- and data-intensive applications more efficiently compared to existing platforms. Currently, data centers (DC) and high performance computing clusters are dominated by power, thermal, and area constraint...

8th July 2016
Electroadhesive clutch substitutes conventional ones in robotics

When Steve Collins first envisioned the electroadhesive clutch, he made a prototype with a sandwich bag and a couple of pieces of aluminum foil from his kitchen. Since creating that makeshift prototype, he and his research team have developed a sophisticated, functional device that can be used in exoskeletons that compensate for a person's disability or enhance their athletic performance.

26th May 2016
Fall-prevention sensors enhance senior care

Carnegie Mellon University's College of Engineering conducted a survey on falls among the elderly, and discovered that Americans are very worried about their elderly parent falling—and that this worry leads to action. Every 13 seconds, an older adult is treated in the emergency room for a fall. Every 20 minutes, an older adult dies from a fall-related trauma.

18th May 2016
Robot's in-hand eye maps surroundings & determines location

Before a robot arm can reach into a tight space or pick up a delicate object, the robot needs to know precisely where its hand is. Researchers at Carnegie Mellon University’s Robotics Institute have shown that a camera attached to the robot’s hand can rapidly create a 3D model of its environment and also locate the hand within that 3D world.

17th May 2016
Turning the entire lower arm into a touchpad

Since the advent of smartwatches, technologists have been looking to expand interactions beyond the confines of the small watch face. New technology developed by the Human-Computer Interaction Institute’s (HCII) Future Interfaces Group at Carnegie Mellon University suggests turning the entire lower arm into a touchpad.

30th March 2016
Internet on a chip: energy-efficient multicore chips

In their recent paper, "Wireless NoC for VFI-enabled multicore chip design: performance evaluation and design trade-offs", researchers from Carnegie Mellon's Department of Electrical and Computer Engineering and Washington State University identify a new approach for enabling energy-efficient multicore systems.

11th February 2016
Robotically driven system could reduce cost of drug discovery

Researchers from Carnegie Mellon University have created the first robotically driven experimentation system to determine the effects of a large number of drugs on many proteins, reducing the number of necessary experiments by 70%. The model, presented in the journal eLife, uses an approach that could lead to accurate predictions of the interactions between novel drugs and their targets, helping to reduce the cost of drug discovery.

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