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Industrial robots, in terms of hardware structure, primarily consist of motor-driven arms and joints. However, as the demands on robots continue to rise (see Table 1), they are no longer just mechanical tools. Modern robots must also possess "intelligence," "vision," and even "mobility." This evolution involves advanced technologies such as perception, operation, communication, action, and even artificial intelligence, making them more versatile and capable.
Artificial Intelligence and Deep Learning in Robots
When discussing a robot's "brain," artificial intelligence (AI) is at the core. Robots are evolving not only through hardware improvements but also through breakthroughs in analytical technologies, enabling higher levels of autonomy and intelligence. Due to the high development barriers in AI, most major investments come from leading technology companies. These firms have launched AI platforms, such as Google’s DeepMind’s AlphaGo and Intel’s Nervana, which are driving innovation in robotic systems.
AlphaGo, known for its mastery of the game of Go, uses deep learning based on neural networks for estimation, prediction, and decision-making. When applied to industrial robots, this technology allows machines to detect and sort workpieces automatically based on their shape and ease of handling. This represents a significant step forward in the integration of deep learning into industrial automation.
Sensory Capabilities and Machine Vision
The sensory capabilities of a robot are essential for its interaction with the environment. One of the most common senses is vision, which has become a standard feature in many industrial robots. As electronic components shrink, human eyes can no longer perform precise assembly and inspection tasks. Therefore, machine vision systems—equipped with high-precision detection capabilities—have become vital in applications such as measurement, positioning, guidance, and object recognition.
According to a report by Insight Partners, the market for machine vision systems is expected to grow from $7.5 billion in 2015 to $14.48 billion by 2025. These systems use optical devices and software algorithms to simulate human visual perception and judgment. They typically include image processors, cameras, sensors, and lighting sources, along with software that processes images and recognizes 3D objects.
An example of this is the laser weeding robot developed by the University of Bonn in Germany, which uses a photographic identification system to distinguish weeds from crops and then eliminates them using a laser. This kind of application highlights how machine vision is transforming agriculture and industrial automation.
Many companies in Taiwan are also investing heavily in machine vision. For instance, Solomon’s self-developed 3D vision module enables robots to identify and sort workpieces in complex environments. Advantech’s EagleEye solution helps manufacturers with real-time quality control and barcode scanning, while also providing guidance for robotic arms during part handling.
Pain Sensation: Protecting the Robot
To prevent damage, some robots now have a "sense of pain." Researchers at the German Institute for Humanoid Robotics have developed a robotic arm that mimics human skin structure, giving it a form of tactile sensitivity. When the robot detects pain, it reacts accordingly—retracting slowly for mild discomfort, quickly moving away for moderate pain, and entering passive mode for severe pain to minimize damage.
Intelligent Manufacturing and the Future of Robotics
The progress in sensing technologies like machine vision is largely driven by the push toward intelligent manufacturing. From isolated points to integrated lines and full-scale production, the influence of robotics is expanding across industries. Robotic arms now often have machine learning capabilities, and improved control systems and circuit designs allow for higher robot density in production lines. Through digitization and big data, robots are becoming more flexible and adaptable.
However, the development of industrial robots also comes with challenges. Cybersecurity is a growing concern, especially given the increasing reliance on automation. If hacked, robots could cause serious damage, not just to equipment but potentially to human lives. As we continue to enhance robot functionality and productivity, we must also ensure they are secure against cyber threats.
Yixing Futao Metal Structural Unit Co. Ltd. is com manded of Jiangsu Futao Group.
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