Robotic surgery system with dynamic ai arbitration and risk-driven autonomy

A robotic surgical system configured for safety-based autonomy transitions, comprising:

• a control system configured to execute autonomous or semi-autonomous surgical functions;
• a safety transition engine configured to:
• monitor operational metrics including AI confidence, sensor fidelity, task complexity, and patient-specific physiological parameters;
• compute a cumulative uncertainty index over a sliding time window;
• compare the uncertainty index to task-specific safety thresholds;
• initiate transition from autonomy to reduced-autonomy or manual mode when thresholds are exceeded;
• log contextual data including system state, procedural phase, surgeon response, and environment variables for postoperative review and model refinement.

A robotic surgical system comprising:

• a surgeon console operatively connected to a local robotic arm assembly;
• a context monitoring module configured to assess real-time operational parameters including network latency, intraoperative stress indicators, system health metrics, and procedural phase;
• a multimodal arbitration engine configured to:
• dynamically allocate control between AI-driven autonomy and surgeon-directed manual operation based on context monitoring outputs;
• implement a phase-adaptive control policy that increases surgeon control during high-risk procedural phases and enhances AI autonomy during routine or repetitive tasks;
• adjust levels of autonomy including passive AI guidance, constrained execution, or full autonomy based on predefined safety policies and real-time indicators;
• a fallback controller that ensures seamless transition to surgeon-only manual control if any of the operational parameter exceeds predefined risk thresholds;
• a contextual audit log storing arbitration decisions, associated context data, and surgeon override activity for postoperative analysis and system learning.