A Framework for High Precision Robotic Arms Using Control Systems and Algorithmic Intelligence

Our project provides a systematic approach to enhancing the precision of robotic arms by combining smart control hardware and intelligent algorithms. PID control, adaptive schemes, and model-based schemes provide precision by making adjustments continuously by using feedback. Machine learning and artificial intelligence also provide adaptability using online tuning, best path planning, and natural human-robot interfaces. Additional refinement by reinforcement learning and machine vision allow enhanced autonomy and system optimization. This combined framework achieves optimal accuracy, fiexibility, reliability over a wide range of uses, from medical operations to manufacturing machines.