How Robosurf uses AI to improve the performance of its Robots

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Artificial Intelligence (AI) in physical robotics and computer vision has been steadily increasing in recent years, leading to significant advancements in these fields.

Vision & AI

Artificial Intelligence (AI) in physical robotics and computer vision has been steadily increasing in recent years, leading to significant advancements in these fields.”

Robosurf 


In our autonomous mobile robotic for construction, AI has been used to improve the performance and capabilities of the robots in rough environments on construction sites. For example, machine learning algorithms have been used to train the robots to recognize and classify objects, allowing them to manipulate and interact with their environment more effectively. AI has also been used to develop robots that are able to learn through trial and error, allowing them to adapt to new tasks and environments more quickly.

One of the main benefits of using AI in our autonoums mobile robots is the ability to automate tasks that are either too dangerous or too tedious for humans. This has led to the development of robots that can work in difficult or hazardous environments where workers are at high risk of accidents or danger to health.
In addition to supporting workplace safety, Robosurf construction robots are able to perform tasks that require a high level of precision in a consistent and efficient manner.


Are you wondering how businesses use AI? Then check out McKinsey’s State of AI in 2022. It examines the adoption and investment of Artificial Intelligence over the last 5 years, plus tips on implementation. Explore the data here.


The use of AI at Robosurf has also been making an impact in the field of computer vision. Computer vision is the ability of computers to interpret and understand visual data from the world around us. This can include tasks such as image and video recognition, object detection, and facial recognition.

In our case, AI is used to improve the accuracy and efficiency of computer vision tasks for our autonomous mobile construction robots. For example, machine learning algorithms have been used to train systems to recognize and classify objects in images and videos with a high degree of accuracy. This has a wide range of applications, including obstacle recognition, positioning optimization, safety and quality improvement, and the implementation of inspection processes.
Overall, the adoption of AI in our physical robotics for construction and in combination with computer vision has led to significant advancements in the optimization of our robots to increase performance on construction sites. 

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