See how collaborative robots can help fight the epidemic
Outbreak protection, robots in action!
In this battle without gunpowder, there are both retrogrades and guardians. However, more and more "black technologies" have begun to show their skills and become a powerful weapon against viruses! Intelligent robots are not only able to measure body temperature, sterilize and avoid obstacles, but also deliver meals to patients. They replace manual work, which not only improves work efficiency, but also effectively reduces the risk of infection for medical staff.
How do robots achieve these same operating functions as humans? Today Xiaoke will talk about the important characteristics of robots: teachability.
Teachability of collaborative robots
The control and logic of the robot are combined with its mechanism. If you think about it, this is also a human characteristic. My son is learning to tie shoelaces and he knows how to do it; he can lead me up the steps, but his body is not doing well yet. He is still in the kinesthetic learning phase. His muscle memory for sensation, touch, grip and adjustment has not yet been developed. For industrial robots, we are still in the early stages of robotics. This is not to say that without smart people putting these together, these newer robots will have similar problems as our children. The company will program the robot's brain and determine how to put decision logic in the controls, but the robot's mechanism still needs to learn kinesthetic feedback like a human.
For example, people tend to use some tricks when you pick up a large bag of sugar from the table. It usually involves sliding the bag so that your hand wraps around the smaller part of the bag and completes the lifting action. This is easy for adults, but it is a challenge for children with smaller hands. Suppose a collaborative robot can pick up that bag of sugar. How difficult is it? Will it use another arm or tool to slide its end effector under the bag? Will it slide the bag to the end of the table and balance it at the end and then lift it? Will the gripper be larger than the human hand, and will it decide to pick up the sugar packet from a wider area? Finally, how much squeezing force will it use? It needs sufficient squeezing force to lift the sugar packet, but It should not be too strong, so as to prevent the paper bag from breaking and causing sugar to spill out.
I think, like human children (and adult kinesthetic process learning), teaching robots will be based on trial and error and trial and error. The collaborative robot will lift the bag of sugar multiple times. Bags need to be placed on the table in different ways-horizontally, tiled, diagonally, upright, etc. Once the collaborative robot can pick up the sugar bag, can he pick up other objects, such as almonds? Can it pick up almonds without damaging the almonds? For the end user, the robot needs to be easy to teach and the robot's learning process Also quickly. All work depends on the design of the robot control system and the cooperation of robot joints and mechanical devices to complete the physical work.
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