An Articulated Continuum Robot for Turbine Blade Inspection With Kinematics Enabling Constraint-Aware Motion Planning and Execution

Abstract

In typical operational scenarios such as turbine blade inspection, robots are subject to complex spatial constraints and are prone to mechanism—environment interference, which restricts their motion and may even render them inoperative. To address this issue, this paper proposes a novel 10-degree-of-freedom (10-DOF) continuum robot configuration and, on this basis, develops a bounded nonlinear least-squares (NLS) inverse kinematics (IK) framework for precise motion control under joint limits and tube-shaped workspace constraints. Specifically, a tube-aware rapidly-exploring random tree connect (RRT-Connect) planner is first employed to compute a coarse joint-space path with edge-wise feasibility checking; then, sequential least squares programming (SLSQP) refines it into a smooth skeleton; finally, follow-the-leader (FTL) performs dense Cartesian micro-stepping via bounded NLS, while enforcing segmented virtual-tube soft constraints along link-sampled points. Simulation results in CoppeliaSim demonstrate that the proposed method generates smooth and safety-compliant trajectories in confined environments and robustly tracks the target blade edge curve, effectively mitigating branch jumping and orientation discontinuities. Quantitative metrics, including tracking root-mean-square error (RMSE), tube-margin, violation statistics, and per-step computation time, indicate favourable feasibility and stability. Overall, this work provides an effective joint solution for global–local trajectory planning and constrained IK of redundant continuum robots in strongly constrained cavity inspection tasks.