When walking around with a scalding hot cup of coffee, you probably spend most of your time thinking, “I hope I don’t spill this scalding hot coffee on myself!” And most of the time, you’re successful. But how? From all the joints in your arm, wrist, and fingers to the liquid in the cup that is not directly in your control, it’s an extremely complex system humans handle with relative ease. But what if you had to build a robot to do the same task? Would you trust that poor robot not to spill coffee on itself?
Analysing how humans carry a cup of coffee might seem like the world’s most boring gig, but for engineers working in robotics, it’s an important next step towards creating machines that can handle more human tasks. “While humans possess a natural, or gifted, ability to interact with complex objects, our understanding of those interactions — especially at a quantitative level, is next to zero,” Ying-Cheng Lai, an electrical engineering professor at Arizona State University, explained.
So they’re trying to learn. A team of researchers from ASU’s School of Electrical, Computer and Energy Engineering has published a paper entitled “Synchronous Transition in Complex Object Control” that builds on previous research that examined how humans handled a rolling ball in a cup — a system modelled after carrying a cup of hot coffee. What that study found is that people tended to use two methods for controlling the ball — and they sometimes even switched between the two. The ASU team’s research further analysed how that subtle transition happens. “The findings from this study can be used to implement these human skills into soft robots with applications in other fields, such as rehabilitation and brain-machine interface,” Lai added.
So though carrying coffee makes for a good theoretical example, this research isn’t about building an army of coffee-serving robots. (Sorry, Starbucks!) Instead, it’s about taking a task humans find easy and figuring out how to make it less difficult for machines.
“A systematic quantitative understanding of how humans interact dynamically with their environment will forever change how we engineer our world, and may revolutionise the design of smart prosthetics and usher in a new age of manufacturing and automation,” Brent Wallace, a doctoral student and co-author of the paper, stated. “By mimicking the dynamically-favourable behaviours adopted by humans in handling complex objects, we will be able to automate processes previously thought to be impossible.”
This story first appeared on www.foodandwine.com
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