The Role Of AI in The Evolution Of Industrial Robotics

Robotics and software Engineers around the world are striving to improve the learning capabilities of industrial robots. This comes after all manufacturing, and service-based companies started introducing automation-induced streamlining of their workflow to reduce production and export time. Industrial robots today are being taught via machine learning algorithms to perform monotonous chores such as welding, assembly, disassembly, pick and place for printed circuit boards, packaging and labelling, palletising, product inspection, testing, etc. 

Program algorithms need to be manually updated every time a new or modified task is to be assigned to the robots. However, as they are incapable of tackling unidentified errors or remembering previously performed actions for long terms, it becomes mandatory to rewrite the robot’s memory programming multiple times for a multi-step task. This becomes quite painstaking overtime as it consumes a lot of time and doesn’t improve the machine’s abilities in any way. What the robots really need for better performance is the ability to self-learn and analyse the problems related to their tasks. And this is where Artificial Intelligence(AI) comes in. 

If we consider ML data as the objects of a robot’s memory, then AI is what gives it the ability to comprehend those objects as analytical information. This symbiotic relationship between ML and AI plays a prominent role in the evolution of IoT based technology, and now, it is being implemented in the training culture of industrial robots.

Here’s how the combination of AI and ML works:

• The training data provided to the robot via ML tells the robot what exactly the task is and what rules are to be followed.
• An AI infrastructure helps the robot to:

• understand those rules and find the most optimal way of performing that task
• Learn from its actions to avoid or solve unforeseen errors
• Develop its own new set of rules for solving newly discovered errors without conflicting the original set of rules
• Utilise the steps learned from one task to perform other similar tasks without any reprogramming.

Consider the example of bin picking task. To train a robot with computer vision technology, it was provided with a set of sample images of the sorted objects to pick out various objects from a bin and sort them based on certain factors. After analysing those images, the robot was not only able to sort the known objects but was also able to use its newly learned strategies to sort other unknown objects too. The robot was even able to pick out specifically required objects from the mixed bin.

This way, the engineers will be able to focus more on optimising tasks instead of training the robots. One set of AI infrastructure is enough for training multiple robots, simultaneously making it easier to assign different robots for different jobs in less time. 

To develop a proper understanding of these newly emerging AI applications, it is essential to gain in-depth information on the fundamental concepts of AI. and to do so, what you need is an organisation that specialises in providing AI solutions and conducting exhaustive AI and robotics courses.

If you’re curious about the upcoming robotic technologies and are looking for such robotics courses in Pune, then India First Robotics is where you’ll find all your answers. As one of the top robotics manufacturers in Pune, the team at India First Robotics provides extensive hands-on training right from scratch in the form of well-curated robotics training institute in Pune. To learn more about their technology and products, visit their website today.