As students and administrators seek anytime, anywhere access to the cloud, higher ed IT teams must face their fears and get to work.
From government to finance to education, it seems that everyone wants to work in the cloud these days — even robots.
As cloud computing captures the public imagination, it also has become the latest area of serious study in robotics on numerous college campuses, including Philadelphia's Drexel University and the University of Minnesota.
James Kuffner, a research scientist at Google, purportedly coined the term "cloud robotics" in 2010 to describe "a new approach to robotics that takes advantage of the Internet as a resource for massively parallel computation and sharing of vast data resources," writes the University of California, Berkeley's Ken Goldberg.
The goals, primarily, are twofold: Use cloud-based applications for data processing and storage capability, freeing up a robot from having to lug all that technology around with it, and enable robots to communicate and share data among themselves.
Among those interested in the emerging field is M. Ani Hsieh, an assistant professor in the mechanical engineering and mechanics department at Drexel University, and the head of Drexel's robotics program. Hsieh recently co-hosted a National Science Foundation and U.S. Army Research Laboratory–sponsored workshop on cloud robotics, along with Ibrahim Volkan Isler, an associate professor at the University of Minnesota. Much of Hsieh's research focuses on large-scale sampling of oceans to predict currents, and how changes in the ocean impact weather. The group hopes to eventually take advantage of cloud robotics in that research, she says.
"For us to be able to move in that direction, we must first understand how current ocean models are generated and how to transition this into the cloud computing framework," Hsieh says. "From there, we will have to address the question of how information and data obtained by robots and other stationary sensors in the ocean can be assimilated into these cloud models in real time.
"Once we have addressed the data assimilation problem, then we need to answer the prediction portion. So, our work is still very much at its infancy," Hsieh says.
At the University of Minnesota, Isler is using robots to track a slightly smaller water prey — the common carp, "an invasive species of fish that poses a significant threat across the Midwest," Isler says. "It is important to track and control the species."
To that end, Isler's department leads a collaborative project, funded by the National Science Foundation, to build a network of robotic devices that can be used to locate and track carp that carry radio-frequency ID tags. The project brings together roboticists, computer systems experts, mathematicians and marine biologists to tackle problems ranging from optimal search and active tracking with multiple robots to more energy-efficient operations and general understanding of fish behavior.
Isler also is interested in learning more about how the cloud could free his robots from having to carry the processors needed to store and process data, and the ability to use the cloud as a "super computer," he says.
UC Berkeley's Goldberg says cloud robotics could improve performance in several ways, not the least of which is enabling greater indexing of Big Data, parallel grid computing on demand for statistical analysis, and crowdsourcing.