Striving to enhance the efficiency of computer numerical control (CNC) machining tools used in green converter stations, in this paper, we introduce an innovative approach leveraging multisensor fusion data for the optimal control of a machine’s motion along each coordinate axis. The proposed method focuses on the optimal control of the machine’s motion along each coordinate axis, while considering constraints of precision, speed, and acceleration. A trajectory planning method synthesizing linear interpolation, circular interpolation, and a novel circular arc transfer algorithm is employed. Unlike traditional techniques, our S-curve acceleration and deceleration control model for path segments does not mandate identical start and end speeds for a single path. The model’s efficacy was validated through simulation experiments on a rounded rectangular cutting path, with sensor data simulating real-time machining conditions. The results demonstrated that accounting for instantaneous machining speed and acceleration aids in achieving maximum machining speed more rapidly. Our sensor-informed optimal control algorithm ensured a seamless kinematic transition at the path’s intersection, minimizing abrupt speed changes, which elevated the efficiency of the CNC tool’s motion, markedly reducing the process time. This contribution serves as a major advancement in optimizing CNC machining, promising considerable time efficiency in production.