Needle steering systems have shown potential ad-
vantages 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 con-
troller, 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.