Application of AI in robotics boosts enterprise potential | TechTarget (2024)

Feature

The combination of AI and robotics has allowed companies to move past automation and tackle more complex and high-level tasks with their robots.

Physical robots have been around for almost a hundred years, but not without their limitations. In the 1990s the idea of the collaborative robot, or cobot, emerged to help find ways to put robots in closer proximity to humans, but it is only through the inclusion of AI that robotics can continue to progress.

While the term robotics conjures up visions of hardware machines performing a wide range of tasks, the term robot is now used to describe any sort of software or hardware-based automation that can perform a task.

However, many of these software robotics systems are limited in their ability and are not able to communicate with other systems or robots to carry out these tasks. With the addition of machine learning, robots and cobots can improve their communication and handle even more complex tasks without the normal risk associated with simpler bots.

Cobots and software

Cobots are physical robots that are intentionally designed to operate in close quarters with humans. They are finding increasing use in a variety of different settings, performing pick-and-pack warehouse activities, delivery of goods, and a variety of assistive roles. Increasingly, we are seeing cobots in places as diverse as retail stores, museums, hotels, hospitals and even inside homes.

In this context, robotic process automation (RPA) refers to those software automations that perform repetitive user interface-based tasks that would otherwise be performed by a human, such as typing, clicking, swiping, copying and pasting, and a range of UI-based interactions.

But, if a form layout changes, or additional fields of information are required, these bots are not able to process and handle these exceptions and changes, causing them to fail and making them very brittle.

How AI and machine learning are working with robotics

What makes a robot powerful is an ability to think on its own. This is where artificial intelligence and robotics can come together. Companies are increasingly looking for robots to move past automation and tackle more complex and high-level tasks.

AI can help a robot do a lot of tasks, from successfully navigating their surroundings, to identifying objects around the robot or assisting humans with various tasks such as bricklaying, installing drywall or robotic-assisted surgeries.

Robots can benefit from AI and machine learning in different ways, and these AI-enabled capabilities include:

  • Computer vision. AI and computer vision technologies can help robots to identify and recognize objects they encounter, help pick out details in objects and help with navigation and avoidance.
  • AI-enabled manipulation and grasping. Long considered a difficult task for robots, AI is being used to help robots with grasping items. With the help of AI, a robot can reach out and grasp an object without the need for a human controller.
  • AI-enhanced navigation and motion control. Through enhanced machine learning capabilities, robots gain increased autonomy, reducing the need for humans to plan and manage navigation paths and process flows. Machine learning and AI help a robot analyze its surroundings and help guide its movement, which enables the robot to avoid obstacles, or in the case of software processes, automatically maneuver around process exceptions or flow bottlenecks.
  • Real-world perception and natural language processing. For robots to have some level of autonomy, they often need to be able to understand the world around them. That understanding comes from AI-enabled recognition and natural language processing. Machine learning has shown significant ability to help machines understand data and identify patterns so that it can act as needed.

In the past, researchers have long thought about how to apply artificial intelligence to robotics but ran into limitations of computational power, data constraints and funding. Many of those limitations are no longer in place, and as such, we now may be entering a golden age of robotics. With the help of machine learning, robots are becoming more responsive, more collaborative, and integrated into other systems.

Likewise, many of the RPA vendors are adding intelligent process automation to their bots to help increase their usefulness. As such, they are looking at AI technologies such as NLP or computer vision to help make these bots more intelligent. Bots that leverage machine learning and adapt to new information and data can be considered intelligent tools that can significantly impact and increase the tasks performed rather than just bots.

Growth of robotics

The use of robots in many industries is becoming increasingly common. These robots can either be physical robots or software bots. It is estimated that there will be 3 million industrial robots in operation during 2020. Furthermore, Gartner projected that RPA software spending was over $1.3 billion in 2019. As such, the need and desire for bots of all sorts is seemingly only to going to increase.

Examples of AI powered robotics include: robotic surgery tools that are able to assist surgeons, law enforcement bomb robots that are able to navigate into dangerous terrain to minimize human injury and casualty, and food and package sorting robots that are able to sense different materials and properly pick and sort the objects.

With the use cases seemingly limitless and cutting across many sectors, there is much innovation still to be had and the robotics industry isn't going away anytime soon. Many companies are finding increasing value, efficiency and accuracy from bringing robots into their various operations. This stems from the proof of ROI in the industry and, as people continue to feel more comfortable working with robots, companies will continue to invest in the technology. The addition of artificial intelligence into robotics its making them more useful than ever before.

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Application of AI in robotics boosts enterprise potential | TechTarget (2024)

FAQs

Application of AI in robotics boosts enterprise potential | TechTarget? ›

With the help of AI, a robot can reach out and grasp an object without the need for a human controller. AI-enhanced navigation and motion control. Through enhanced machine learning capabilities, robots gain increased autonomy, reducing the need for humans to plan and manage navigation paths and process flows.

How AI will help in the robotics application? ›

Applications of AI in Robotics

Manufacturing: AI-powered robots automate tasks like assembly, welding, and quality control, improving efficiency and accuracy. Healthcare: Surgical robots assist doctors with minimally invasive procedures, while other robots help with patient care and rehabilitation.

What are the positive effects of AI and robotics? ›

Increased Efficiency: AI can automate repetitive tasks, improving efficiency and productivity in various industries. Data Analysis and Insights: AI algorithms can analyze large data quickly, providing valuable insights for decision-making.

How AI and robotics will affect the future of work? ›

How Will AI Affect Jobs - How many jobs will AI replace by 2030. Artificial intelligence (AI) could replace the equivalent of 300 million full-time jobs, a report by investment bank Goldman Sachs says. It could replace a quarter of work tasks in the US and Europe but may also mean new jobs and a productivity boom.

What are the potential applications of robotics? ›

Different Robot Applications in Industries

In material handling industries where finished products are prepared for distribution, robotics are used for picking, sorting, packaging and palletizing of products. Other industries that commonly use robotics include clinical laboratories, agriculture and education.

Why is AI important in robotics? ›

AI helps robots sense and perceive through various sensors, such as cameras, touch sensors, distance sensors to detect their surroundings, identify objects and make decisions based on this information. Use of Data within the robots and bundle with AI application for predictive maintenance and decision making .

How AI will change robotics? ›

These technologies will drive the evolution of robots, making them more autonomous and capable of complex tasks. Generative AI, a branch of machine learning, will significantly enhance robot vision, enabling robots to better understand and interact with their environment.

What are the pros and cons of AI robotics? ›

But beyond the headlines that either peddle hype or fear, what does AI do? The advantages range from streamlining, saving time, eliminating biases, and automating repetitive tasks, just to name a few. The disadvantages are things like costly implementation, potential human job loss, and lack of emotion and creativity.

What is the conclusion of AI in robotics? ›

Conclusion. The integration of AI in robotics has had a significant impact on various industries, revolutionizing processes, improving efficiency, and enhancing safety.

How might AI and robotics change our future lives? ›

On the positive side, AI and robots can make daily tasks at home easier, improve work efficiency, and contribute to creating sustainable cities. They might work alongside humans, becoming helpful partners in creating a safer and more efficient environment. However, there are challenges.

What jobs will robots AI replace in the future? ›

“Examples include data entry, basic customer service roles, and bookkeeping.” Even assembly line roles are at risk because robots tend to work faster than humans and don't need bathroom breaks. Zafar also points out that jobs with “thinking” tasks are more vulnerable to replacement.

What is the future of AI and robotics? ›

Future robotics and automation might serve as assistants, workmates, teachers, surgeons, and explorers. As engineers and scientists continue to develop and advance robotics, the capabilities of this technology will only increase. In many ways, robots are already an integral part of daily life.

What is an example of application of AI in robotics? ›

AI can predict the future movement of objects or obstacles in the environment of robots. It enables them to adapt to a dynamic environment and make decisions in real-time. Self-driving vacuums and cars are examples of Autonomous navigation.

What are two real world uses applications for robotics? ›

General Benefits of Robots in Daily Lives

Robots are able to carry out tasks in hazardous environments such as the inside of a nuclear power plant or deep underwater. They can also shield humans from dangerous situations by working alongside us, such as flying planes or driving cars.

What is an example of AI in robotics? ›

A drone might use autonomous navigation to return home when it is about to run out of battery. A self-driving car might use a combination of AI algorithms to detect and avoid potential hazards on the road. All these are the examples of artificially intelligent robots.

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