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Industrial robots, in terms of hardware structure, primarily consist of motor-driven arms and joints. However, as the demands placed on robots continue to rise (see Table 1), modern robots are no longer just mechanical tools—they need "intelligence," "vision," and even "senses." This evolution involves advanced technologies such as robot perception, operation, communication, action, and even artificial intelligence, making today’s industrial robots far more capable than their predecessors.
Artificial Intelligence and Deep Learning in Robots
When discussing a robot’s "brain," artificial intelligence (AI) is an essential component. The development of robotics has evolved beyond mere hardware upgrades; it now includes breakthroughs in analytical technologies that enable higher levels of intelligence. Due to the high barriers to entry in AI, major investments in this field are typically made by large technology companies. These firms have launched various AI platforms, such as Google's DeepMind’s AlphaGo and Intel’s Nervana platform, which are designed for complex decision-making and learning tasks.
AlphaGo, known for its success in playing Go, uses deep neural networks for estimation, prediction, and decision-making. When applied to industrial robots, these techniques allow them to detect objects, classify them, and even sort items based on ease of handling. This represents a significant leap forward in robotic capabilities, showing how deep learning is transforming the industry.
Sensory Capabilities and Machine Vision
The sensory aspect of robots plays a crucial role in enabling them to interact with their environment. One of the most common senses for robots is vision. As electronic components become smaller and more complex, human eyes can no longer perform precise assembly or inspection. This has led to the widespread use of machine vision systems, which are now standard in many industrial robots. These systems are used for tasks like measurement, positioning, guidance, and object identification.
According to a report by Insight Partners, the market for machine vision system components and integration is expected to grow from $7.5 billion in 2015 to $14.48 billion by 2025. Machine vision systems combine optical devices and software algorithms to simulate human perception of the three-dimensional world. They include hardware such as image processors, cameras, sensors, and lighting sources, along with software that performs image processing and 3D object recognition.
For example, the laser weeding robot developed by the University of Bonn in Germany uses a photographic identification system to distinguish weeds from crops in fields. Once identified, the robot uses a laser to target and weaken the weeds, preventing their growth. Similarly, companies like Solomon have developed 3D vision modules that help robots identify and sort workpieces in cluttered environments. Advantech’s EagleEye solution also supports real-time quality control and barcode scanning, helping robots perform more efficiently.
Pain Sensing: Protecting the Robot
In addition to vision and intelligence, some robots now have a "sense of pain" to protect themselves from damage. Researchers at the German Institute for Humanoid Robotics have developed a robotic arm that mimics human skin, equipped with a "neural machine organization" system that allows it to detect discomfort. When the robot senses pain, it reacts accordingly—retreating slowly if the pain is mild, moving away quickly if it's moderate, and switching to passive mode if the pain is severe. This feature helps prevent further damage and ensures safer interactions with the environment.
Intelligent Manufacturing and the Future of Robotics
The advancement of sensing technologies like machine vision is largely driven by the trend toward intelligent manufacturing. As industries move from isolated automation to integrated smart systems, robots are becoming more flexible, efficient, and adaptive. Modern robotic arms often come with built-in machine learning capabilities, while improved control systems and circuit designs allow for higher robot density in production lines. Through digitization and big data, robots are gaining greater flexibility and responsiveness.
However, the development of industrial robots also presents challenges. Issues such as efficiency, accuracy, and safety must be addressed. With robots increasingly replacing human labor in large-scale production, they are also potential targets for cyberattacks. If compromised, they could cause not only financial loss but also serious harm to people. As we push the boundaries of what robots can do, it's crucial to ensure they are secure and reliable.