AI and kinematics

We see robotic mechanisms in our everyday lives. It is a huge industry that is actively developing and becoming more sophisticated every year. But many people wonder how robots know exactly how to move, where to go, and where to pick up things. Inverse kinematics is the science that explains how robots precisely calculate the movements of their joints to achieve the desired goal. Until recently, inverse calculations were based on very complex mathematics and required considerable computing power.

But with the invention and development of artificial intelligence, all that has changed, it has become the most advanced technology for controlling robots. It has many performance advantages, such as precise control and shorter computation time, in addition to overcoming several mathematical problems in motion and path generation.

In practice, the main challenge in motion control of a robot arm has been to find an accurate and reliable solution for inverse kinematics. The calculation of inverse kinematics is essential for real-time control, and the solution of the inverse kinematics is a computationally complex process that requires particularly long processing times, as well as a combination of geometric, iterative, analytical, and algebraic approaches.

Recently, a lot of attention has been given to artificial intelligence-based methods for solving inverse kinematics problems of general-purpose robots. According to the research results, artificial neural networks provide higher computational accuracy and achieve optimal control of robot motions in Cartesian coordinates.

Of course, training a neural network to build kinematic calculations is not an easy task. After all, artificial intelligence requires thousands of training examples before it can make accurate calculations. However, scientists are already actively using new approaches to learning, for example, the transfer learning method is particularly popular. It dramatically reduces the number of training images required.

Artificial intelligence continues to evolve. And it is having an impact on the development of other areas of science. Thanks to AI, robotic machines are learning to move faster and their activity is becoming more advanced.

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