How AI and machine learning can improve robotics

In the current era, artificial intelligence is changing the world by its applications, which almost expanded to every sector. AI is making the world automated by providing ease to human work in any industry we can imagine. Machine learning, which is a subset of AI, is mostly used in daily life problem-solving. We can see that machines are replacing humans in daily routines and can work faster than humans. So, robotics is one of the industries where AI has its massive impact, which pertains to the following areas:

  • Vision
  • Text processing
  • Audio

In vision-related problems, artificial intelligence helps in automating the robotic industry to detect anomalies and vulnerabilities, grasping different items in the warehouse, for instance. Moreover, NLP (Natural Language Processing) helps develop chatbots that significantly ease the communication process with potential clients and improve customer experience. In this article we will cover the following:

  • Contribution of AI in robotics
  • How AI in robotics makes manufacturing more efficient
  • Use cases of AI and robotics
  • Key insights

Contribution of AI in robotics

The combination of AI and robotics is extremely powerful as it helps automate multiple business processes. AI, with its learning abilities and flexibility, has become a common solution in robotics. Here are more details on how AI assists robotics:

Path planning

AI makes it possible for robots to move precisely in complicated and unexpected environments. As long as the objects and their spatial location are known and specified, traditional robots, for example, have the capability of picking objects along a predetermined trajectory.

AI plays a vital role in the path planning of robots in a complex environment. It enables robots to find the shortest path and to avoid any hurdle on their way. AI algorithms and occlusion detection make it possible for robots to move in complex environments with ease, which enables the development of automatic cleaning, delivery, and a vast variety of other robots.

Activity recognition

Activity recognition is used in many computer vision-related applications, including information retrieval, robotics, real-time monitoring, and event classification. The task of activity recognition has been greatly improved by deep learning architectures that can be trained by utilizing large and comprehensive datasets. Firefighting, door opening, theft prevention robots are only a few examples where activity recognition prevails.

Control systems

Robots are being used in games as AI-based algorithms make it possible for the robots to adapt to the environment and play the game accordingly by analyzing the strategy of the opponent. This contributes to the development of autonomous games, which are increasingly popular.

How AI in robotics makes manufacturing more efficient?

Industrial manufacturers are wondering how to use artificial intelligence to streamline their operations. Some companies, for example, rely on AI to create components that supplement robotics, like printed circuit boards (PCB). A 20–25-micron layer of conductive electro-deposited copper is required by each component hole on its walls, which makes the process of manufacturing a multilayered PCB extremely difficult. New robots could be brought to the market by applying artificial intelligence for PCB manufacturing or design. Some AI robotics businesses also reduce the time it takes for robots to learn their tasks, which helps speed up production. FANUC recently introduced a new approach for teaching industry robots in a faster and more efficient manner.

Moreover, AI makes the whole procedure of getting robots ready for the warehouse floor much easier. To educate the bot on what to pick and what to discard, the users just need to click on images of desired objects from the monitor. What is more, a self-diagnosing robot is revealed by OMRON, which can detect when repairing or maintenance is required. This self-diagnosing robot can also make production more efficient by preventing interruption triggered by malfunctioning kit.

Use cases of AI and robotics

AI is the ultimate bedrock for robotics that has managed to find application in industries as diverse as autonomous vehicles, marketing, social media, and so on. Let’s take a closer look at a few examples below:

Autonomous cars

Artificial intelligence is the main pillar in self-driving cars. Constant monitoring of the surroundings is carried out by the sensors that are put in these vehicles and then necessary modifications are made using artificial intelligence.

Every millisecond, thousands of data points like car speed, pedestrian location, etc., are gathered by these sensors and then AI is used to analyze the data to make corresponding decisions.

Social media monitoring

Social media platforms are in a constant race to create personalized and meaningful experiences for consumers. Artificial intelligence has the potential to make or break the industry’s future. Because of its capacity to organize enormous amounts of data, recognize photographs, introduce chatbots, and foresee emerging trends, AI has become pivotal to this industry of billions of users. The integration of AI and ML can have a profound impact on an industry that is under pressure to regulate fake news, hate speech, and other factors in real-time.

Automatic robotic invigilator

ARI has been developed by merging artificial intelligence and robotics. Vision and AI algorithms are used to monitor student behavior during exams. ARI senses the environment by using a camera stream and reporting when a student moves their heads in the wrong direction.

Key insights

Artificial intelligence doesn’t cease to revolutionize the robotic industry too with its applications. Robots now solve complex problems in our daily lives more efficiently. AI algorithms in path planning, for instance, foster the development of self-driving cars. Artificial intelligence and machine learning are pushing robotics forward by making improvements in terms of safety, and model longevity. Moreover, AI and ML are increasing the efficiency of the robotics industry by giving robots capabilities of vision, text, and audio recognition.

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