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Ultrasound Tracking and Closed-Loop Control of a Magnetically-Actuated Biomimetic Soft Robot

Artur João Anjos de Oliveira, Jorge Batista, Sarthak Misra, Venkatasubramanian Kalpathy Venkiteswaran

Year
2022
Citations
11

Abstract

Small untethered soft robots have potential for diverse applications, particularly in constrained spaces where the use of a tethered device would be infeasible. Examples include biomedical applications such as brachytherapy, fine-needle biospy and micro-needle drug delivery. To advance soft robots towards these applications, there is a need to establish methods for tracking and control using clinically-relevant methods. This study demonstrates motion planning and magnetic control of a soft untethered robot, using ultrasound images as feedback. The closed-loop control of the Millipede soft robot is first validated using a camera-based tracker, where the deviation between the planned path and the trajectory of the robot is 1.71 mm. Afterwards, two methods for ultrasound-based tracking capable of estimating the pose of the robot are proposed, a geometric approach and a convolutional neural network (CNN), and their performance is compared using a video camera as ground truth. Following this, the CNN method replaces the camera tracker to estimate the position and orientation of the robot. The closed-loop system using ultrasound images guides the robot through the workspace while avoiding virtual obstacles, and achieves an average tracking error of 1.59 mm and an angle error of 2.24°.

Keywords

Computer visionArtificial intelligenceComputer scienceRobotWorkspaceConvolutional neural networkTracking (education)Orientation (vector space)TrajectoryTracking system

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