Planning and Optimization of Adaptive Milling Trajectories in Robotic Manipulators

Abstract

In the era of advanced automation and smart manufacturing, robotic manipulators are increasingly employed for complex tasks such as adaptive milling. This paper presents an in-depth investigation into the planning and optimization of milling trajectories in robotic manipulators with an emphasis on adaptivity to surface topology and process dynamics. By integrating real-time sensor feedback and trajectory adjustment algorithms, our approach improves machining accuracy, tool life, and overall production efficiency. Simulation results and comparative performance metrics confirm the superiority of the proposed method over conventional fixed-path planning.