Real-time Vision-guided Online Trajectory Generation for Industrial Robots Using Dynamic Look-Ahead and NURBS Interpolation

Under complex industrial conditions such as illumination variation, partial occlusion, and dynamic tool-workpiece contact, industrial humanoid robots require visuoperception-driven online trajectory generation for high-precision embodied manipulation. This paper proposes a real-time vision-guided online trajectory planning framework based on dynamic reverse look-ahead and piecewise NURBS reconstruction, which enables continuous trajectory updating without predefining complete reference paths. An eye-in-hand camera is adopted for real-time image acquisition, and trajectory points are efficiently extracted through ROI discretization and reverse path look-ahead. A quadratic Taylor expansion based interpolation scheme is further developed to achieve high-precision real-time interpolation with a 2 ms cycle on a real-time Linux and IgH-EtherCAT platform. Tracking experiments are conducted on three types of trajectories (line, random B-spline curve, and circular arc), with each trajectory repeated five times under different initial conditions. The proposed method achieves smooth and continuous online tracking, with an average tracking error below 0.5 mm and a maximum error below 1.0 mm. Moreover, ablation results show that the proposed reverse look-ahead strategy reduces the mean tracking error by approximately 30% and suppresses error oscillations compared with the baseline without look-ahead. The planning loop maintains a stable millisecond-level computational cost, validating its real-time capability for closed-loop visuoperception-driven manipulation. The experimental results validate the effectiveness of the proposed framework on a 6-axis industrial manipulator for real-time vision-guided path tracking. The current findings are most directly applicable to industrial path-following tasks such as welding, grinding, and spraying, while extension to humanoid robots should be regarded as a potential future direction that requires additional validation under whole-body balance and task coordination constraints.