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Related Experiment Video

Updated: Jan 16, 2026

Dynamic Navigation for Dental Implant Placement

Dynamic Navigation for Dental Implant Placement

Published on: September 13, 2022

Real-Time Motion Compensation for Dynamic Dental Implant Surgery.

Daria Pisla¹, Vasile Bulbucan², Mihaela Hedeșiu¹

¹Department of Maxillofacial Surgery and Radiology, Oral Radiology, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania.

Journal of Clinical Medicine

|September 27, 2025

Summary

This study introduces a real-time motion compensation system for dental implant surgery. It uses optical tracking and a collaborative robot to maintain precise tool alignment despite patient head movements, enhancing surgical safety.

Keywords:

computer-assisted oral surgery dental implants machine learning oral surgery robot-assisted oral surgery

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Last Updated: Jan 16, 2026

Dynamic Navigation for Dental Implant Placement

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Published on: September 13, 2022

Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla

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Published on: October 18, 2021

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Published on: August 5, 2021

Area of Science:

Robotics in Medicine
Surgical Navigation Systems
Biomedical Engineering

Background:

Accurate instrument positioning is crucial for dental implants, especially in complex anatomy.
Traditional navigation systems struggle with patient head movement during surgery.
Dynamic conditions necessitate adaptive solutions for maintaining surgical tool accuracy.

Purpose of the Study:

To propose and validate a real-time motion compensation framework for dental implant procedures.
To integrate optical motion tracking with a collaborative robot for dynamic tool alignment.
To enhance precision and stability in robot-assisted dental surgery.

Main Methods:

A six-camera optical system tracked markers on a head model.
Real-time pose data guided a collaborative robot (Kuka LBR iiwa) for tool alignment.
Motion compensation involved inverse trajectory computation and filtering, tested with precise robotic movements.

Main Results:

The system demonstrated low pose tracking errors (<0.2 mm) and tool center point deviations (<1.5 mm).
Average system latency was approximately 25 ms, with minimal overshoot.
The robot exhibited stable and repeatable motion compensation across various dynamic conditions.

Conclusions:

The developed framework reliably compensates for real-time head motion in dental implantology.
It maintains high positional accuracy and stability during dynamic surgical scenarios.
This technology has the potential to significantly improve surgical safety and precision.