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In a step toward home-helper robots that can quickly navigate unpredictable and disordered spaces, University of Michigan researchers have developed an algorithm that lets machines perceive their environments orders of magnitude faster than similar previous approaches.
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At yesterday’s May 2019 University of Michigan Board of Regents’ meeting, several Core and Affiliated Robotics faculty were approved for promotions to associate and full professors, both with tenure.
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Beginning in 2018, Talia Moore, a postdoctoral fellow in ecology and evolutionary biology, with the help of Shai Revzen, Robotics core faculty, organized partnerships between Robotics and departments around the university to invite speakers whose research demonstrates the interdisciplinary nature of the field, creating the “Robotics Interfaces” seminar series.
Talks have spanned research on how ants navigate to 3D printing in architecture and fashion. Despite the various origins of such research, such as biology, architecture, or design, all presented topics have implications for robotics. For example, Barbara Webb’s research of navigation in ants includes building computational models of the ant’s neural processing. She then uses these models to test and replicate the navigational behavior in small, ant-like robots.
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Last year, California experienced the single largest wildfire in its recorded history, a wildfire in Greece killed 100, and wildfires in the British Columbia surpassed the historic proportions seen only the year before. Water and firebreaks can fight immediate threats, but improved mapping and better planning in deploying such resources can maximize impact and minimize risk, reducing the impact of fires over an entire season.
One way to improve mapping and firefighting plans? Unmanned aerial vehicles (UAVs) and algorithms that allow them to operate autonomously.
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If a driver does not trust an autonomous driving system, letting the computer take control can be as daunting as letting a teenager take the wheel. While not trusting a new driver might cause passengers to slam a phantom brake pedal or white-knuckle an arm rest, a driver who does not trust driverless systems might miss out on important safety benefits or even, as autonomous system advance, the ability to complete other tasks.
To improve trust in autonomous systems, researchers at the University of Michigan conducted virtual driving trials that found that the more information an automated driving system communicated about upcoming situations, the higher the level of trust a driver had in the system, and the better the driver performed on a task other than driving.
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