This paper presents a semi-automatic system for robotically assisted 2D needle steering that uses duty-cycling to perform insertions with arcs of adjustable curvature radius. It combines image feedback manually provided by an operator with an adaptive path planning strategy to compensate for system uncertainties and changes in the workspace during the procedure. Experimental results are presented to validate the proposed platform.

This paper presents an adaptive approach for 2D motion planning of steerable needles. It combines duty-cycled rotation of the needle with the classic Rapidly-Exploring Random Tree (RRT) algorithm to obtain fast calculation of feasible trajectories. The motion planning is used intraoperatively at each cycle to compensate for system uncertainties and perturbations. Simulation results demonstrate the performance of the proposed motion planner on a workspace based on ultrasound images.