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Task Automated Stereotactic Brain Biopsy Robotic System With CLF-CBF-Based Safety-Critical Neuronavigation

Yitian Xian, Yichong Sun, Xiao Luo, Yingbai Hu, Limin Zou, Danny Tat Ming Chan, David Chan, Zheng Li

Year
2025
Citations
4

Abstract

For stereotactic brain biopsy, some neurosurgical robots have been adopted to provide the level-1 autonomy (mechanical guidance). However, their surgical safety and collaboration with surgeon still remain challenges. To answer these problems, this article presents a robotic system with higher autonomy in this procedure. First, for level-2 (task) autonomy, a novel brain biopsy device is developed based on the requirements of surgical hygiene, task automation, and intuitive control. Second, for level-3 (conditional) autonomy, a safety-critical, collision-free, and workspace-constrained neuronavigation is achieved, with each proposed objective and constraint formulated by control Lyapunov functions (CLFs) and control barrier functions (CBFs). Specifically, for dynamic collision avoidance with surgeon, the Robo-centric Euclidean signed distance field method is extended and integrated with the time-variant CBF. An optimal-decay CLF-CBF-based quadratic programming framework is utilized to unify and solve these tasks. For evaluation, simulations and experiments are designated and conducted. Results demonstrated that the proposed solution can realize the collision-free and workspace-constrained neuronavigation when the nearby surgeon performs surgical tasks, and offer the biopsy samples sufficient for histopathological examination. This research contributes to higher autonomy of brain biopsy robotic system, by bringing a facilitation of surgeons' operation, an alleviation of their physical/mental burden, and an enhancement of surgical safety.

Keywords

Brain biopsyNeuronavigationTask (project management)Stereotactic biopsyComputer scienceMedicineMedical physicsRadiologyBiopsyMagnetic resonance imaging

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