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Tokekar receives National Science Foundation grant for collaborative robot studies | ECE | Virginia Tech

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Tokekar receives National Science Foundation grant for collaborative robot studies

Aravind Premkumar (MSCPE '17 ) and Ashish Budhiraja (MSCPE '17) work in Tokekar's Robotics Algorithms & Autono-mous Systems (RAAS) Lab.

Aravind Premkumar (MSCPE '17 ) and Ashish Budhiraja (MSCPE '17) work in Tokekar's Robotics Algorithms & Autono-mous Systems (RAAS) Lab.

Pratap Tokekar

Pratap Tokekar's research explores how heterogenous teams of robotsaerial, ground-based, and water-basedcan sense their surroundings and autonomously decide what kind of robot should be deployed where.

A ground-based robot exploring a room can survey a floor plan and crawl under a table, but it won't be able to see off the roof. By working with an aerial robot, however, the two can collaborate to form a complete map of the area.

"Designing algorithms to autonomously explore an environment with a team of heterogeneous robots is a notoriously hard problem in robotics," said ECE assistant professor Pratap Tokekar.

Tokekar received a $175,000 grant from the National Science Foundation (NSF) Computer and Information Science and Engineering Research Initiation Initiative to explore this problem.

Heterogeneous systems like these, he explained, force the robots to make decisions about what kind of robot to send to explore which areas, and how much information they need to exchange. With the grant, Tokekar and his team will investigate the coordination of different robotic sensors as they attempt to collectively observe an environment from all viewpoints.

The study will build on one of Tokekar's related projects, which investigates how robots could be used in precision agriculture. He has been developing aerial and ground-based robots that collaborate to collect data on farms, particularly nitrogen levels. By noting areas of nitrogen deficiency, farmers can use this information to guide the timing and amount of fertilizer application.

For a robot to be able to autonomously decide how to behave in situations like these, it needs to make sense of a lot of information from multiple sources, explained Tokekar. Meeting this challenge requires knowledge from many disciplines, including mechanical engineering, electrical and computer engineering, and computer science. "If you can bring in tools and techniques from more than one area, the impact will be so much better," he said. "There is a strong interplay between machine learning, control systems, and robotics."

With this new grant, Tokekar and his team will explore the combination of robotic assignment and routing problems with diversity constraints. "These investigations lay the foundations to achieve the overarching goal of understanding the role of diversity in robot swarms," said Tokekar.