Enhancing Behavior Planning for Robotic-Assisted Techniques in Urologic Oncology

Linjian Huang^1,2Miaoran Li³Xin Xu¹Zhijian Xie^2*

• ¹The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
• ²Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Hangzhou, China
• ³Hangzhou Dental Hospital West Branch, Hangzhou, China

Background: The integration of robotic-assisted techniques in urologic oncology offers new opportunities to enhance surgical precision, contextual awareness, and safety. However, conventional robotic systems lack real-time adaptability and cognitive decision-making capabilities. Objectives: This study aims to develop an intelligent behavior planning framework that enables context-aware, multimodal, and interpretable decision-making for robotic-assisted urologic surgeries. Method: We propose a novel hybrid framework that integrates pre-trained multimodal transformers with surgical ontologies and real-time feedback mechanisms. The system includes a Neuro-Surgical Transformer (NST) for phase recognition and intent inference, and a Cognitive-Aware Adaptive Execution (CAAE) module for safe and dynamic task execution. Results: Extensive simulation and phantom experiments across four public datasets demonstrate that our framework reduces planning time by 25% and improves procedural accuracy by 15% compared to state-of-the-art methods. It also enhances robustness under uncertainty and improves responsiveness during critical surgical events. Conclusions: The proposed method significantly improves autonomous behavior planning in robotic-assisted urologic oncology. It provides a scalable, interpretable, and adaptable solution that bridges expert reasoning and machine execution.