Adaptive path planning for steerable needles using duty-cycling
Mariana C. Bernardes, Bruno Vilhena Adorno, Philippe Poignet, Nabil Zemiti, Geovany A. Borges · 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems · 2011
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.