Sensorless Remote Center of Motion Misalignment Estimation

2025-03-17

AI Summary

In laparoscopic robotic surgery, manual trocar placement, patient motion, and tissue deformation frequently cause misalignment between the remote center of motion (RCM) and the incision site, generating damaging forces at the port. To address this, we propose a sensor-free framework for real-time RCM misalignment estimation and compensation. Leveraging only robot joint torques and kinematic data, our method employs dynamic modeling and interaction force inversion to estimate RCM offset purely in software—eliminating reliance on hardware calibration or external sensors. Experimental evaluation demonstrates an absolute estimation error ≤5 mm for misalignments ≥20 mm; furthermore, we empirically verify that misalignments exceeding 20 mm induce clinically significant tissue damage risk. This work presents the first intraoperative, hardware-free solution for online geometric RCM misalignment assessment and compensation, establishing a foundational capability that substantially enhances surgical safety and robustness.

Technology Category

• Intelligent Robots: State Estimation
• Computer Vision: Motion & Tracking
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Laparoscopic surgery constrains instrument motion around a fixed pivot point at the incision into a patient to minimize tissue trauma. Surgical robots achieve this through either hardware to software-based remote center of motion (RCM) constraints. However, accurate RCM alignment is difficult due to manual trocar placement, patient motion, and tissue deformation. Misalignment between the robot's RCM point and the patient incision site can cause unsafe forces at the incision site. This paper presents a sensorless force estimation-based framework for dynamically assessing and optimizing RCM misalignment in robotic surgery. Our experiments demonstrate that misalignment exceeding 20 mm can generate large enough forces to potentially damage tissue, emphasizing the need for precise RCM positioning. For misalignment $Dgeq $ 20 mm, our optimization algorithm estimates the RCM offset with an absolute error within 5 mm. Accurate RCM misalignment estimation is a step toward automated RCM misalignment compensation, enhancing safety and reducing tissue damage in robotic-assisted laparoscopic surgery.

Problem

• Estimates RCM misalignment without sensors
• Reduces unsafe forces at incision sites
• Improves safety in robotic laparoscopic surgery

Innovation

• Sensorless force estimation for RCM misalignment
• Dynamic assessment and optimization algorithm
• Automated RCM misalignment compensation enhancement