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Nathan A Wood¹, Kevin Waugh², Tian Yu Tommy Liu¹

¹The Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.

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Summary

This study introduces a novel framework for the HeartLander miniature epicardial crawling robot to precisely locate itself on a beating heart. The system accurately estimates robot position, heart pose, and cardiac phase using electromagnetic tracking and a dynamic heart model.

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Area of Science:

Robotics
Biomedical Engineering
Medical Imaging

Background:

Accurate localization of robotic instruments on the beating heart is critical for minimally invasive cardiac procedures.
Existing methods often rely on complex imaging or invasive sensors, posing challenges for miniature robots.

Purpose of the Study:

To develop and validate a framework for localizing the HeartLander robot on a beating heart using limited sensor data.
To simultaneously estimate the robot's position, the heart's pose, and its physiological phase.

Main Methods:

Development of motion and observation models based on 6-DOF electromagnetic position tracking data.
Implementation of a particle filter for state estimation.
Simulation using a dynamic 3-D human heart model and a HeartLander robot motion model.

Main Results:

The particle filter framework accurately estimated the HeartLander's position on the epicardial surface.
The system successfully determined the heart's pose in the world coordinate frame.
Accurate estimation of the heart's physiological phase was achieved.

Conclusions:

The proposed framework enables robust localization of the HeartLander robot on a beating heart.
This approach integrates robot pose, heart pose, and physiological phase estimation effectively.
The demonstrated simulation results show promise for real-world applications in cardiac interventions.