The Rise of AI in Robotics

AI-enabled robots are superior to non-AI machine, as these robots are capable of performing certain tasks while adapting to their environment. Therefore, AI-empowered robots are more intelligent than other machines. One can use training to make the computer understand physical and logistical data patterns. It can act according to its environment, robots are also integrated with various functions like computer vision, motion control, and grasping objects.
Post Header Image
Ananya Avasthi
March 24, 2022
March 24, 2022
October 29, 2021
Post Detail Image

The first known automated type machines people understood were robots. In earlier times robots were designed with a specific task in mind. These were machines that were developed earlier without any artificial intelligence (AI) to perform only repetitive tasks. As technology has advanced, AI is being integrated into robots rapidly. This is, of course,  to develop robotics that can perform multiple tasks, and also analyze new situations with a better perception of the environment. 

AI-enabled robots are superior non-AI machine as these robots are capable of performing certain tasks has the ability to adapt in its environment, therefore, is more intelligent than other machines. One can use training to make the computer understand physical and logistical data patterns. It can act according to its environment, robots are also integrated with various functions like computer vision, motion control, and grasping objects. In order to understand certain situations or to locate the various objects, labeled The AI model is trained with the assistance of machine learning (ML). Image annotation (image annotation is a tool for visualizing and searching unstructured data. Enterprise-grade image annotation tools are made for fast, easy, and accurate labeling) plays a key role in creating a colossal bank full of datasets that help robots to recognize and grasp different types of objects. 

Application of Machine Learning in Robotics

Machine learning is used in training an AI model, it is used to increase the level of intelligence of the AI. AI should be able to perform specific tasks or some varied actions. A set of data is used at a large scale to ensure that the AI  models can perform precisely. To achieve that, multiple datasets are fed to the ML algorithms. Practice makes perfect, the more rigorous the training, the higher is the accuracy of the AI model.

Usually, AI-enabled robots are trained to recognize the objects, with the capacity to grasp the same object and the affinity to be able to move from one location to another. Machine learning is used to assist in recognizing the wide-ranging objects visible in different shapes, sizes, and various situations. The machine learning process will keep running if the robots detect new objects. This, in turn, creates a new category to detect such objects if visible again shortly. However, there are different ways of teaching a robot using machine learning. Deep learning is also an option to train such models with high-quality training data for a more accurate machine learning process.

Robotics at Warehouses

Warehouse requires a fair amount of manpower to manage the towering amount of inventory kept by mainly eCommerce companies to deliver the products to their customers or move from one location to another. In such scenarios, there are some robots that are trained to handle such inventories with the capability to carefully carry them from one place to another. This reduces the human workforce in performing such repetitive tasks.

Robotics in Healthcare

An automated solution in the medical industry and other divisions in the industry is becoming increasingly popular. AI companies are now using big data and other relevant datasets from the healthcare industry, using machine learning to creating different types of training models for different purposes. The variety ranges from medical supplies to sanitization, disinfection, and performing remote surgeries. AI in robotics is pushing machines to become more intelligent as it learns from the data and performs crucial tasks without the assistance of humans.

Robotics in Agriculture

Automation is assisting the farmers to improve crop yield and boost productivity. Robots play a significant role in the cultivation and harvesting. Robots have the ability to precisely detect plants, vegetables, fruits, crops, and other unwanted floras. In agriculture AI robots can execute fruit or vegetable plucking, spraying pesticides, and supervise the health conditions of plants.

Robotics in Automotive

The automobile industry has already reached a level of fully automated assembly lines to assemble the vehicles. Most of the major operations that handled by robotics to develop cars, in turn, reducing the cost of manufacturing. Robots are specially trained to perform certain actions with immense accuracy and efficiency.

Application of AI in Robotics

Combining AI with robotics creates machines that are more efficient with self-learning ability to recognize new objects. As of now, robotics are usually applied for industrial purposes and in various other fields to perform various actions. These actions are more accurate and are at higher efficiency than human workers. These tasks range from handling the carton boxes at warehouses to robots performing unbelievable actions to create easier means of completing the task at hand.

Want to learn more about AI?

GPT-3 is considered the most recent advancement of AI

Though they may not be robots, NLP is becoming the fuel of chatbots

NLP is being used to battle misinformation

"Most comprehensive labelling tool in the market. Datasaur has saved us countless hours in building our own solution. My team lead never wants to go back to spreadsheets!"

G2 Reviewer

"Operating in an industry where we have to be privacy- and security-conscientious with our data, Datasaur was the only acceptable solution for us. We recommend them for both feature set and support responsiveness."

G2 Reviewer

"...information labeling tasks has been reduced by 80% which has allowed us to optimize our workflow much more, allowing us to focus on other areas that are also priorities for us..."

Mary L