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Adaptive path planning for steerable needles using duty-cycling
Acte de colloque

Adaptive path planning for steerable needles using duty-cycling

Mariana C. Bernardes, Bruno V. Adorno, Philippe Poignet, Nabil Zemiti, Geovany A. Borges et IEEE
Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2545-2550
IEEE International Conference on Intelligent Robots and Systems
01/01/2011

Résumé

Computer Science Computer Science, Artificial Intelligence Computer Science, Information Systems Engineering Engineering, Electrical & Electronic Robotics Science & Technology Technology
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.

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