artificial intelligence (AI) is driving the robotics market into various areas, including mobile robots on the factory floor, robots that can do a large number of tasks rather than being specialized on one, and robots that can stay in control of inventory levels as well as fetching orders for delivery.
Such advanced functionality has raised the complexity of robotics. Hence the need for AI.
Artificial intelligence provides the ability to monitor many parameters in real-time and make decisions. For example, in an inventory robot, the machine has to be able to know its own location, the location of all stock, know stock levels, work out the sequence to go and retrieve items for orders, know the location of other robots on the floor, be able to navigate around the site, know when a human is near and change course, take deliveries to shipping, keep track of everything, and more.
The mobile robot also has to interoperate with various shop floor systems, computer numerical control (CNC) equipment, and other industrial systems. AI helps all those disparate systems work together seamlessly by being able to process their various inputs in real-time and coordinate action.
Autonomous robots market
The autonomous robotic market alone is worth around $103 billion this year, according to Rob Enderle, an analyst at Enderle Group. He predicts that it will more than double by 2025 to $210 billion.
“It will only go vertical from there,” Enderle said.
That’s only one portion of the market. Another hot area is robotic process automation (RPA). It, too, is being integrated with AI to deal with high-volume, repeatable tasks. By handing these tasks over to robots, labor costs are reduced, workflows can be streamlined, and assembly processes are accelerated. Software can be written, for example, to take care of routine queries, calculations, and record keeping.
Historically, two different teams were needed: one for robotics and another for factory automation. The robotics team consists of specialized technicians with their own programming language to deal with the complex kinematics of multi-axis robots. Factory automation engineers, on the other hand, use programmable logic controllers (PLCs) and shop floor systems that utilize different programming languages. But software is now on the market that brings these two worlds together.
Further, better software and more sophisticated hardware has opened the door to a whole new breed of robot. While basic models operate on two axes, the latest breed of robotic machine with AI is capable of movement on six axes. They can be programmed to either carry out one task, over and over with high accuracy and speed, or execute complex tasks, such as coating or machining intricate components.
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5 Examples of AI in robotics
Honda’s ASIMO has become something of a celebrity. This advanced humanoid robot has been programmed to walk like a human, maintain balance, and do backflips.
But now AI is being used to advance its capabilities with an eventual view toward autonomous motion.
“The difficulty is no longer building the robot but training it to deal with unstructured environments, like roads, open areas, and building interiors,” Enderle said. “They are complex systems with massive numbers of actuators and sensors to move and perceive what is around them.”
2. Sight Machine and Nissan
Sight Machine, the developer of a manufacturing data platform, has partnered with Nissan to use AI to perform anomaly detection on 300 robots working on an automated final assembly process.
This system provides predictions and root-cause analysis for downtime.
See more: Artificial Intelligence: Current and Future Trends
3. Siemens and AUTOParkit
Siemens and AUTOParkit have formed a partnership to bring parking into the 21st century.
Using Siemens automation controls with AI, the AUTOParkit solution provides a safe valet service without the valet.
This fully automated parking solution can achieve 2:1 efficiency over a conventional parking approach, AUTOParkit says. It reduces parking-related fuel consumption by 83% and carbon emissions by 82%.
In such a complex system, specialized vehicle-specific hardware and software work together to provide smooth and seamless parking experience that is far faster than traditional parking. Siemens controls use AI to pull it all together.
Kawasaki has a large offering of robots that are primarily used in fixed installations. But now it is working on robotic mobility and that takes AI.
“For stationary robots to work seamlessly with mobile robots, it is essential that they can exchange information accurately and without failure,” said Samir Patel, senior director of robotics engineering, Kawasaki Robotics USA.
“To meet such integration requirements, Kawasaki robot controllers offer numerous options, including EtherNet TCP/IP, EtherNet IP, EtherCat, PROFIBUS, PROFINET and DeviceNet. These options not only allow our robots to communicate with mobile robots, but also allow communication to supervisory servers, PLCs, vision systems, sensors, and other devices.”
With so many data sources to communicate with and instantaneous response needed to provide operational efficiency and maintain safety, AI is needed.
“Over time, each robot accumulates data, such as joint load, speed, temperature, and cycle count, which periodically gets transferred to the network server,” Patel said. “In turn. the server running an application, such as Kawasaki’s Trend Manager, can analyze the data for performance and failure prediction.”
5. Sight Machine and Komatsu
Sight Machine, in close cooperation with Komatsu, has developed a system that can rapidly analyze 500 million data points from 600 welding robots.
The AI-based system can provide early warning of potential downtime and other welding faults.