Recently, Huawei’s talented boy Zhihui Jun made an Iron Man robotic arm, which has aroused heated discussions among netizens. It is said that this is the most complicated project he has done so far. The name of the robotic arm is also very interesting- it’s called “Dummy”. Not only is it a tribute to Iron Man’s robotic arm, it is also a “guidance point” bound to the end of the robotic arm, implying Zhihui Jun’s careful thoughts.
Dummy uses Huawei Harmony operating system and Centerm Atlas processor, and its body color is China red. Apart from its beautiful appearance, Dummy is also very powerful. It has a special and practical method of interaction. In addition to the traditional computer input instructions, graphical phase machine, manual teaching and other methods, Zhihui Jun also added a display screen to Dummy, which can intuitively see the action of the robotic arm and control it through a wireless connection.
But Zhihui Jun is still not satisfied. The modified handheld remote has a force feedback motor, which can not only control the gripper of the robot forward, but also feel the strength of the grasping remotely when grasping the object. Using such a set of devices that can remotely feel the control force, this robotic arm achieves a powerful “surgery” capability similar to a Da Vinci robot, such as performing a suture operation on grapes.
But after all, Zhihui Jun, who has the aura of “Wild Iron Man at Station B”, said that this is his most complicated project (takes 4 months), and the degree of hardcore is definitely more than that. The real situation is — this robotic arm is all made by Zhihui Jun, both inside and out!
With the help of AI technology, traditional industrial equipment has basically achieved breakthrough. Based on computer vision, AI can be trained to detect appearance defects and dimensions of industrial products, quickly reduce inspection costs, and improve inspection speed and accuracy.
On the production side, machine vision simulates human vision through a computer, and processes and understands based on the extracted information. As the complexity of industrial production continues to deepen, more and more micro-machining production processes continue to emerge, followed by a large amount of uncontrollable wear and consumption. In order to ensure production accuracy, machine vision is widely used in processes such as dimensional measurement and positioning of parts and process automation.
Loading and unloading robots can accurately transfer materials, collaborative robots complete flexible and efficient human-machine collaboration, and storage robots transfer flexible materials and products etc. They are common manifestations of automated robots bringing new productivity and efficiency to the production process.
On the inspection side, the traditional inspection link is usually completed manually, which has problems such as low inspection efficiency and relatively high recognition error rate. Machine vision is a big progress, but still face the problems of high customization costs, long cycles, and complicated parameter calibration.
AI uses image processing technology to identify and uses trained models to perform quality inspections, reducing labor costs and improving accuracy. The AI + machine vision inspection program has good scalability and uniform standards, and can reduce labor costs and improve inspection efficiency.
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