Forbidden Region Dynamic Active Constraints in Robot-Assisted Minimally Invasive Surgery

2026-08-03

AI Summary

This work addresses dynamic tissue deformation caused by respiratory motion in robot-assisted minimally invasive surgery by proposing an energy-passive active constraint method for forbidden regions. The approach integrates real-time depth camera sensing, high-density dynamic mesh modeling (comprising 122,806 polygons), and energy-dissipative control to deliver anisotropic force feedback guidance. This ensures operational safety while preserving computational efficiency. The system operates in real time at 43.48 Hz and, in ex vivo experiments, consistently maintained the prescribed safety margin with 100% success. Compared to conventional geometric constraint methods, the proposed technique achieves significantly improved guidance performance with comparable or lower computational overhead.

Abstract

In robot-assisted surgery, Forbidden Region Active Constraints (FRAC) represent a control strategy that helps maintain task safety by generating anisotropic haptic guidance to surgeons. However, several challenges need to be overcome before FRAC can benefit teleoperative surgery in a clinical setting. These challenges include the ability to allow for dynamic tissue deformation, maintain energetic passivity, and speed of implementation, among others. In this study, we propose the pipeline design for an energy dissipative FRAC strategy, which accommodates the dynamic tissue deformation caused by respiratory movements, by utilizing a depth sensing camera. The proposed FRAC strategy adopts a fine mesh representation, with a total number of 122,806 polygons in the case study presented, while running at 43.48Hz. We designed in vitro trajectory tracking experiments conducted by a "virtual" surgeon to aid quantitative assessment of the method, including its effectiveness in maintaining task safety, which was confirmed by successfully maintaining a pre-defined safety distance across all trials. We also conducted comparative studies to investigate the robustness and time-efficiency of our method against other FRAC methods that rely on simple geometry AC representations. We demonstrate that our method provides a more robust and effective guidance overall, while maintaining comparable, if not lower, time costs.

Problem

• Forbidden Region Active Constraints
• dynamic tissue deformation
• robot-assisted surgery
• energetic passivity
• safety

Innovation

• Forbidden Region Active Constraints
• dynamic tissue deformation
• energy dissipative control
• depth sensing
• haptic guidance