The CNC machining of molds and various 3D parts involves numerous cavity features, and the design of machining toolpaths directly affects machining quality and efficiency. With the advancements in high-speed milling technology, CNC machines provide the hardware foundation for improving cavity machining efficiency, but they also place higher demands on CAM toolpath design. Traditional CAM toolpaths tend to cause abrupt changes in cutting load when dealing with areas such as cavity corners, slots, and intersections of circular paths. This load instability limits the improvement of feed rate and cutting depth, negatively impacting both machining efficiency and quality. To address these issues, this paper proposes a hybrid toolpath planning and feed rate optimization method aiming at achieving constant load machining for cavities. The method, which is based on a multi-level block structure, first calculates the material removal rate and then divides the machining areas into stable, semi-stable and load fluctuation regions. For different regions, circular toolpaths, feed speed optimization and variable-radius trochoidal paths are comprehensively adopted to ensure smooth load control throughout the machining process. By applying trochoidal paths in areas prone to load fluctuations, sudden load variations can be reduced and stable machining process can be ensured. Experimental results show that the proposed toolpath planning and feed rate optimization method is suitable for generating CAM toolpaths for various complex cavities, with good load stability and better machining quality.

Real-time visual and precise haptic interaction algorithms are critical for achieving accurate “tactile sensation” in virtual surgical training. In order to reduce storage space, improve computational efficiency, accurately calculate cutting forces during bone milling, and balance the visual and haptic interaction effect, this paper proposed a visual and haptic interaction algorithm based on the Tri-dexel model. Firstly, the Tri-dexel model was employed to represent the bone and the surgical milling tool. Real-time geometric deformation during the virtual bone milling was achieved through boolean operations and rapid surface reconstruction algorithms. Secondly, by integrating the geometric parameters of the surgical milling tool, a haptic interaction model based on the micro-element cutting force was proposed. This model utilizes the boolean operation results between the bone and surgical milling tool to quickly and accurately solve the instantaneous undeformed chip thickness. Thirdly, the cutting force coefficients were identified and the haptic interaction model was validated through milling experiments to achieve haptic rendering. Finally, an orthopedic virtual surgical training system was built based on the above-mentioned algorithms, and the interaction algorithm was tested and evaluated experimentally. The results show that the predicted forces align with experimental measurements, with an average force error of less than 7%. The visual and haptic interactive algorithm satisfies a visual refresh rate of 30 Hz and a haptic refresh rate of 1 kHz. The developed orthopedic virtual surgical training system provides users with a highly immersive virtual bone milling training experience that can effectively improve users’ hand-eye coordination.