Permanent Magnet-Based Localization for Growing Robots in Medical Applications

Abstract

Growing robots that achieve locomotion by extending from their tip, are inherently compliant and can safely navigate through constrained environments that prove challenging for traditional robots. However, the same compliance and tip-extension mechanism that enables this ability, also leads directly to challenges in their shape estimation and control. In this letter, we present a low-cost, wireless, permanent magnet-based method for localizing the tip of these robots. A permanent magnet is placed at the robot tip, and an array of magneto-inductive sensors is used to measure the change in magnetic field as the robot moves through its workspace. We develop an approach to localization that combines analytical and machine learning techniques and show that it outperforms existing methods. We also measure the position error over a 500mm × 500 mm workspace with different magnet sizes to show that this approach can accommodate growing robots of different scales. Lastly, we show that our localization method is suitable for tracking the tip of a growing robot by deploying a 12 mm robot through different, constrained environments. Our method achieves position and orientation errors of 3.0 ± 1.1 mm and 6.5 ±5.4° in the planar case and 4.3 ± 2.3 mm, 3.9 ±3.0°, and 3.8 ±3.5° in the 5-DOF setting.