Elite collaborative robot was unveiled at the China Industry Fair

Create Date: 2024-8-30 12:03:23|Source: Elibot

On November 7, 2017, the 19th China International Industry Fair with the theme of innovation, intelligence and green was held at the National Convention and Exhibition Center (Shanghai). Elite seven-axis collaborative robot EC75 and artificial intelligence demonstration system have attracted many domestic and foreign industry experts.
Elite collaborative robot was unveiled at the China Industry Fair
  The EC75 is a redundant cobot with an attractive appearance and 7 joints. It uses the degrees of freedom of 7 joints to control 6 attitude variables at the end, so it has a unique zero space, which can make one terminal pose correspond to an infinite combination of joint space, which greatly improves the flexibility of control. Compared with the traditional 6-degree-of-freedom robot, it can also make full use of its redundant degrees of freedom to achieve many unique functions such as avoiding space obstacles, avoiding singular configurations, avoiding the limit of joint angle position, and optimizing the torque of each joint while realizing terminal attitude control.

In addition to the characteristics of redundant robots, EC75 also supports drag teaching functions based on robot dynamics model recognition. Drag teaching is a simple, efficient, and human-machine friendly robot teaching mode. Users can easily drag the robotic arm to the teaching point and reproduce the teaching point or continuous teaching trajectory with one click, which greatly improves the efficiency of teaching programming and lowers the operation threshold of the cobot.

In order to expand the application scope of cooperative robots, the meeting also launched the forward-looking concept of artificial intelligence + cooperative robots, through the embedding of artificial intelligence technology, truly realized human-machine cooperation, human-machine cooperation, and demonstrated the latest research results in this direction - random mixture grasping system and robot laundry folding system.

The random mixture capture system applies the latest deep neural network (DNN) technology, based on the self-developed object recognition and capture posture prediction algorithm, to guide the robot to achieve the correct capture of random rigid objects without obtaining object model data in advance. Through the fusion of 2D and 3D data, the system reduces the accuracy requirements of the depth vision sensor, improves the capture success rate, improves the versatility of the capture system, supports the capture mixture, and is widely used in 3C, logistics, retail, catering and other industries, providing a solid foundation for the capture application of intelligent workers and service robots in industrial environments.

Through deep reinforcement learning (DRL) algorithms and depth vision sensors, the robotic laundry folding system can accurately locate the laundry folding point, with fast positioning speed and high accuracy, and automatically find the best movement trajectory to achieve the perfect laundry folding effect. The simulation environment is used to quickly model and transfer learning (TL) methods to speed up learning, reduce data acquisition costs, and finally reflect the simulation results into real robot operations.

The report of the 19th National Congress of the Communist Party of China pointed out that it is necessary to highlight key common technologies, cutting-edge leading technologies, modern engineering technologies, and disruptive technological innovations. These four technological innovations are the fundamental support for China's construction of a modern economic system, which not only conforms to the laws of contemporary scientific and technological development, but also fully embodies the major needs of modern construction. Technological power has become the current keyword, and national leaders have expressed the importance of scientific and technological power on many occasions.

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