The Application of Artificial Intelligence in Robotic Control

Abstract

The pursuit of automated robotics took shape in the mid-20th century. While industrial robots relied on fixed programs to perform repetitive tasks in structured environments, they faced significant limitations in adaptability and flexibility. By the early 21st century, technological advancements enabled robots to make basic decisions, though complex tasks still required human programming. Following the AI revolution, robots now possess autonomous learning and decision-making capabilities through AI algorithms, transitioning from rulebased to intelligence-driven systems. Current challenges in robotic control primarily involve three aspects: enhancing environmental adaptability in unstructured settings to improve interference resistance, and optimizing real-time coordination efficiency for complex tasks. This paper analyzes the technical principles, practical applications, and countermeasures to address these challenges. It explores how AI can reshape robotic control. Research conclusions indicate that AI holds vast potential in robotic control. Through continuous optimization of technical pathways and resolution of existing issues, comprehensive intelligent upgrades in robotic control are achievable, delivering more efficient and precise automation solutions across industries.