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This story is from the category Artificial Intelligence
Date posted: 03/03/2017 The buzzword in drone research is autonomous — having the unmanned aerial vehicle do most or all of its own flying. It’s the only realistic way that drones will have commercially viable uses such as delivering that roll of toilet paper to customers, said Manish Kumar, associate professor of mechanical engineering at the University of Cincinnati’s College of Engineering and Applied Science. Kumar and his co-authors, Nicklas Stockton, a UC researcher, and Kelly Cohen, aerospace engineering professor, considered the difficulty drones have in navigating their ever-changing airspace in a study presented at the American Institute of Aeronautics and Astronautics SciTech 2017 Conference in January. This problem is compounded when the drone tries to land on a moving platform such as a delivery van or even a U.S. Navy warship pitching in high seas. “It has to land within a designated area with a small margin of error,” Kumar said. “Landing a drone on a moving platform is a very difficult problem scientifically and from an engineering perspective.” To address this challenge, UC researchers applied a concept called fuzzy logic, the kind of reasoning people employ subconsciously every day. While scientists are concerned with precision and accuracy in all they do, most people get through their day by making inferences and generalities, or by using fuzzy logic. Instead of seeing the world in black and white, fuzzy logic allows for nuance or degrees of truth. “In linguistic terms, we say large, medium and small rather than defining exact sets,” he said. “We want to translate this kind of fuzzy reasoning used in humans to control systems.” Fuzzy logic helps the drone make good navigational decisions amid a sea of statistical noise, she said. It’s called “genetic-fuzzy” because the system evolves over time and continuously discards the lesser solutions. Stockton, Kumar and Cohen successfully employed fuzzy logic in a simulation to show it is an ideal system for navigating under dynamic conditions. Stockton, an engineering master’s student who was lead author on the paper, is putting fuzzy logic to the test in experiments to land quadcopters on robots mounted with landing pads at UC’s UAV Multi-Agent System Research (MASTER) Lab. “This landing project is a real-world problem. A delivery vehicle could have a companion drone make deliveries and land itself,” Stockton said. See the full Story via external site: magazine.uc.edu Most recent stories in this category (Artificial Intelligence): 03/03/2017: Application of Fuzzy Logic Teaches Drones to land on Moving Targets |
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