How Humans Walk and Carry a Cup of Coffee Is a Bit of a Physics Mystery

You probably spend the majority of your time walking about with a boiling hot cup of coffee thinking, “I hope I don’t spill this scalding hot coffee on myself!” And, for the most part, you’re successful. But how do you do it? It’s an enormously complex system that humans manage with relative ease, from all the joints in your arm, wrist, and fingers to the liquid in the cup that is not directly under your control. What if you had to design a robot to perform the same function? Would you put your trust in that hapless robot not to spill coffee all over itself?

Analyzing how humans hold a cup of coffee may appear to be the most tedious job in the world, but for robotics developers, it’s a vital step towards designing computers that can perform more human duties. Ying-Cheng Lai, an electrical engineering professor at Arizona State University, noted, “While humans have a natural, or gifted, ability to interact with complicated objects, our comprehension of those interactions — especially at a quantitative level, is near to nothing.”

As a result, they’re attempting to learn. ASU’s School of Electrical, Computer, and Energy Engineering published a paper titled “Synchronous Transition in Complex Object Control” that draws on prior research that looked at how humans managed a rolling ball in a cup, which was modelled after carrying a cup of hot coffee. People prefered to employ two strategies for manipulating the ball, according to the study, and they even swapped between them at times. The research conducted by the ASU team looked into how that small change occurs. “These human skills can be implemented into soft robots with applications in various disciplines, such as rehabilitation and brain-machine interface,” Lai stated.

Despite the fact that carrying coffee is a nice theoretical example, this research isn’t about creating a coffee-serving army. (Please accept my apologies, Starbucks!) Instead, it’s about figuring out how to make an activity that humans find simple easier for machines.

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