Robotics, Expert System, and Fuzzy Logic in Micro AI
Understand the applications of robotics, expert systems, and fuzzy logic within micro AI. Learn how robotics integrate machine learning to improve operations, how expert systems can collaborate with ML for enhanced decision-making, and how fuzzy logic supports data matching and optimization to refine AI-driven product functionalities.
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Specialized use cases of robotics
With robotics, we’re creating physical structures that operate optimally for certain use cases. Some robotics do relate to each other, particularly when we think about teleoperated robots and augmented robots, where there is some overlap. But by and large, these are created specifically for the use case they have. We can think of robotics as the hardware and the incorporation of ML as the software upgrade package.
Let’s take the example of an autonomous robot that is scanning its environment to find the optimal route or chain of events by which to operate. It might be able to derive insights on its own without using ML algorithms to optimize its route, but if it does want to get better over time, maybe its logs can be used to teach it to maneuver more effectively. With teleoperated robots, DL can be used to optimize the speed, strength, or depth at which it’s handling its subjects and quickly build on the best practices surgeons spend decades mastering (to take the example of robotics in surgery). Because ...