The transition from 2D vision to 3D vision represents a technological leap. 2D vision is limited to recognizing the plane information of objects, while 3D vision uses technologies such as laser triangulation, structured light, time-of-flight (ToF), and multi-camera systems to obtain three-dimensional information, including the curvature and spatial coordinates of objects.

By achieving wide field-of-view, high-speed, and high-precision environmental perception, 3D vision technology overcomes the limitations of traditional 2D technology in terms of accuracy and speed. This technological progress meets the industry's higher requirements for precision, speed, and flexibility, significantly expanding the application scenarios of industrial automation.

The various applications and functions of robot vision can be categorized into four basic functions: recognition, measurement, positioning, and detection. Among them, detection is the most challenging, while recognition is the least difficult. 3D vision, in collaboration with industrial robots, is primarily used to guide the movement of robotic arms, with specific applications focusing on detection, various processes, though predominantly in gripping applications. Their functions within manufacturing processes include loading and unloading, stacking, and sorting along with gluing, polishing, welding, etc. 3D vision detection is superior to the human eye, with lower error rates, faster detection speeds, and lower costs after replacing manual labor.

LE Robotics Robot's tunnel reinforcement intelligent production line, with its advanced 3D vision technology, boasts the advantage of precise positioning and automatic generation of accurate welding trajectories. It not only efficiently meets the needs of tunnel reinforcement construction but also significantly reduces hardware costs, facilitating automation and flexible production in the tunnel construction industry.

The end plate automatic production line utilizes automation technology, including an end plate laser cutting machine and an industrial robot guided by 3D vision. This achieves the automated cutting of end plates and high-precision gripping to optimize the production process.

Further improvements are necessary for high-precision workpiece positioning, continuous 24-hour stable operation, and reducing manual labor intensity under the condition of unordered incoming materials.

Through the 3D recognition algorithm, precise positioning of the end plate has been achieved, with gripping accuracy less than 0.1mm, and stable operation for 24 hours.

Using intelligent gripping algorithms, robots can accurately grip and load, improving stability and safety.

Using AGV carts in conjunction with the production line to automatically transport end plates has increased efficiency and reduced labor intensity.

The AGV (Automated Guided Vehicle) places the end plate frame in a specified position, commanded by the visual control center. The 3D camera identifies and guides the robot to grasp the end plate. The end plate is then positioned at the end of the I-beam, and the 3D vision camera recognizes the end for subsequent welding.

Replacing manual labor for end plate handling and positioning in a fast-paced production environment, and efficient collaboration between multiple robots.

1.Through the 3D vision solution, precise gripping and accurate feeding of the end plate have been achieved, overcoming the challenges of high-speed manual work.

2.Using deep learning and hardware-accelerated algorithms, multi-robot collaborative operations for gripping and welding have been achieved, enabling flexible production.

3.No teaching, no programming, intelligent matching of cutting and welding process parameters, and automatic generation of operation trajectories.

In the I-beam welding process, the end plate accurately placed by the gripped robot allows seamless collaborative operations. The 3D vision intelligent welding system scans the workpiece, generates welding trajectories, and performs functions such as extracting complex weld seam features and positioning workpieces.

The core challenges include improving the qualification rate and efficiency of workpiece welding, achieving fully automatic, no-teaching, no-programming flexible welding, and meeting the needs of small-batch production of multiple varieties.

1.The 3D vision system guides robots for precise welding, improving welding quality and production efficiency.

2.Advantages such as no teaching, no programming, and one-key fully automatic flexible welding have been achieved, enabling flexible welding of multiple varieties in small batches.

3.The built-in welding parameter expert database automatically matches welding parameters, achieving efficient welding.