A Path Planning Strategy for Robotic Bronchoscopic Multi-Sample Biopsy

Abstract

Lung cancer is the leading cause of cancer death globally, and early diagnosis via transbronchial biopsy (TBB) improves outcomes. However, conventional bronchoscopes for multiple pulmonary nodules face inefficiencies and operator skill dependency. This paper proposes a path planning strategy for robotic bronchoscopic multi-sample TBB. It abstracts the bronchial tree as a circuit, with lesions as constant resistance bulbs and bronchial branches as resistors with equivalent resistance based on their morphology. Multi-target path planning is transformed into minimizing total circuit resistance, optimizing trajectories to reduce redundant movements of robotic manipulators. Comparing to traditional methods, evaluations show that over 60% reduced movement distance and 76% less operation time are achieved; experiments accomplish over 40% efficiency improvement, enhancing multi-sample TBB efficiency and safety.