Adaptive path-following control for bio-inspired steerable needles

Needle steering systems have shown potential advantages in minimally invasive surgery in soft-tissue due to their ability to reach deep-seated targets while avoiding obstacles. In general, the control strategies employed to drive the insertion use simplified kinematic models, providing limited control of the trajectory between an entry site and a deep seated target in cases of unmodelled tissue-needle dynamics. In this work, we present the first Adaptive Path-Following (APF) controller for a bio-inspired multi-part needle, able to steer along three-dimensional (3D) paths within a compliant medium by means of the cyclical motion of interlocked segments and without the need for duty-cycle spinning along the insertion axis. The control strategy is outlined in two parts: a high-level controller, which provides driving commands to follow a predefined 3D path smoothly; and a low-level controller, able to counteract unmodelled tissue-needle nonlinearities and kinematic model uncertainties. A simulation that mimics the needle's mechanical behavior during insertion is achieved by using an Experimental Fitting Model (EFM), obtained from previous experimental trials. The Simulation results demonstrate the robustness and adaptability of the proposed control strategy.