7 ene 2022 20:39 GMT
The developers claim that the machine can “recognize the intent” of people with an accuracy of 96%.
A group of researchers from China Three Gorges University’s Intelligent Manufacturing Technology Center for Innovation has built a seemingly wearable robot Can read the human mind By monitoring brain waves and muscle activity.
In a study published in the Chinese Journal of Mechanical Engineering and review According to the South China Morning Post, the developers claim that the machine was able to “recognize human intent” with 96% accuracy.
The device was tested on factory workers, who did not need to issue verbal commands or make gestures when they needed a tool or material, as the robot reacted “almost instantaneously”, picking up and delivering the desired thing.
The study authors emphasized that “in modern industrial manufacturing, assembly work accounts for 45% of the total workload and between 20% and 30% of the total production cost,” adding that their robot could Increase assembly line production.
According to the scientists, the use of these types of robots in the real world has been limited, because “their ability to recognize human intent is often imprecise and unstable.”
To get around this limitation, the team of researchers and eight factory workers subjected the robot (which combines a non-invasive brain wave detector with sensors placed on the arms) to “Hundreds of hours of training“.
The brainwave detector understood the volunteers’ intentions with up to 70% accuracy, but the signal was weak and the workers had to “focus hard” for the robot to receive a clear message.
On the other hand, the electrical signals from the muscles collected by the sensors in the arm were more stable They also lost their power The workers are tired.
According to the scientists, the combination of brain and muscle signals helped the robot to predict a person’s intentions with great accuracy.
However, the study notes that when these results are replicated outside the laboratory environment Issues can ariseBecause race and erratic worker movements can affect the quality of signals.
“Travel enthusiast. Alcohol lover. Friendly entrepreneur. Coffeeaholic. Award-winning writer.”