Robots were the first known automated type machines that people became acquainted with. There was a time when robots were developed for specific tasks; yes, such machines were previously developed without the use of artificial intelligence (AI) to perform only repetitive tasks. But now, AI is being integrated into robots in order to develop advanced levels of robotics that can perform multiple tasks and also learn new things with a better perception of the environment.
AI in robotics assists robots in performing critical tasks such as detecting or recognising various objects with human-like vision. Robots are now developed using machine learning training. A large number of datasets are used to train the computer vision model, so that robotics can recognise various objects and carry out the appropriate actions with accurate results. Furthermore, robotics performance is improving day by day as more quality and precise machine learning processes are developed. So, right now, we’re talking about machine learning in robotics and the different types of datasets used to train the AI model developed for robots.
How is Artificial Intelligence (AI) Used in Robotics?
AI in robotics not only aids in the learning of models to perform specific tasks, but also makes machines more intelligent to act in a variety of scenarios. Robots incorporate a variety of functions such as computer vision, motion control, object grasping, and training data to understand physical and logistical data patterns and act accordingly. Labeled training data is used to train the AI model through machine learning algorithms in order to understand the scenarios or recognise the various objects.
Image annotation plays a key role in creating a large amount of datasets that assist robotics in recognising and grasping different types of objects or performing the desired action in the correct manner, allowing AI to be successful in robotics.
The Use of Machine Learning in Robotics
Machine learning is the process of training an AI model to become intelligent enough to perform specific tasks or actions. And, in order to ensure that AI models such as robotics can perform precisely, a large set of data is used to feed the ML algorithms. Because training data will be used to train the model, the accuracy will be optimal. In robotics, it is trained to recognise objects, with the ability to grasp or hold the same object and move from one location to another.
Machine learning primarily aids in the recognition of a wide range of objects visible in various shapes, sizes, and scenarios. And the machine learning process continues to run. If robots detect new objects, a new category can be created to detect such objects if they become visible again in the near future. However, there are various approaches to teaching a robot using machine learning. Deep learning is also used to train such models with high-quality training data in order to achieve a more precise machine learning process.
