Next steps of the Open Source Leg

October 13, 2020
An open source leg on a table with wires and tools
Alejandro Azocar puts the finishing connections together before testing an open-source robotic leg designed by Elliott Rouse. Photo: Robert Coelius, Michigan Engineering

A new paper on the Open Source Leg, an artificially-intelligent bionic prosthetic leg developed by University of Michigan researchers, was recently published in Nature Biomedical Engineering.

The open-source project, launched publicly last year, is meant to ease the research of controls for prostheses by offering an accessible, comparable, and universal platform available to a broad array of scientists and engineers.

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Lab Showcase 2020

October 8, 2020

A handful of labs across the Robotics Institute summarized their latest research efforts, from regenerative peripheral nerve interfaces to virtual reality teleoperation for pancake making.

Explore the videos below, or check out the entire playlist, to discover the breadth of robotics research at Michigan.

Offutt Charitable Trust supports Michigan Robotics

August 7, 2020
LIDAR demo with Damen Provost
Damen Provost (left), Managing Director of the Robotics Institute, explains a LIDAR demonstration to young roboticists at the 2019 FIRST World Championships in Detroit in April 24, 2019.

A portion of a $2.5M gift from the Daniel E. Offutt III Charitable Trust to endow the Computer Science and Engineering Division Chair will support the Managing Director of the University of Michigan Robotics Institute. 

The late Mr. Offutt graduated from the University of Maryland and received an MBA from Columbia University in 1965. His career was as a stock trader. His longtime friend and colleague, Richard Orenstein, made the gift on behalf of the Trust.

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Brain interface pioneers find meaningful signal in the grey matter noise

July 27, 2020
Drastically reducing the power and computation needed to identify our intentions, researchers open up a future of advanced therapies and machines enabled by our thoughts.

By tuning into a subset of brain waves, University of Michigan researchers have dramatically reduced the power requirements of neural interfaces while improving their accuracy. This discovery could lead to long-lasting brain implants that can both treat neurological diseases and enable mind-controlled prosthetics and machines.

The team, led by Cynthia Chestek, associate professor of biomedical engineering and core faculty at the Robotics Institute, estimated a 90% drop in power consumption of neural interfaces by utilizing their approach.

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