This study aims to develop a machining path posture optimization algorithm for robotic wood processing systems, integrating global path smoothing metrics and local constraint metrics, and refines the overall processes of pose optimization, path generation and interpolation, thereby enhancing machining efficiency.
This study begins by analyzing the redundancy in robotic wood processing systems and provides a parametric description based on five-axis linear paths from computer-aided manufacture (CAD/CAM). Global performance metrics are introduced to smooth joint velocity and acceleration, minimizing oscillations. Local constraints are incorporated to ensure path feasibility. A hybrid algorithm combining segmented dynamic programming and sequential quadratic programming (SQP) is proposed to improve computational efficiency. Finally, the smoothing and interpolation steps following pose-optimized path generation are discussed.
Simulation and experimental results demonstrate the effectiveness of the proposed method in improving efficiency, motion smoothness and satisfying performance constraints.
This study provides a systematic process for path generation and optimization method to robotic wood machining systems. By integrating tool posture constraints and proposing a hybrid optimization algorithm, it offers a novel solution to enhance path planning efficiency and practicality, contributing valuable insights for similar robotic applications.
