On Radiation-Based Thermal Servoing: New Models, Controls, and Experiments

Hu, Luyin; Navarro-Alarcon, David; Cherubini, Andrea; Li, Mengying; Li, Lü

doi:10.1109/tro.2021.3119399

Cited by 5 publications

(1 citation statement)

References 43 publications

(56 reference statements)

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“…This procedure could also be automated by the robot manipulator to increase autonomy level. Also, to locate the position of the spinous process more precisely, other forms of sensory information like thermal images could be incorporated for sensor fusion in addition to ultrasound images [33].…”

Section: Discussionmentioning

confidence: 99%

Ultrasound-Guided Assistive Robots for Scoliosis Assessment with Optimization-based Control and Variable Impedance

Duan¹,

Victorova²,

Zhao³

et al. 2022

Preprint

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Assistive robots for healthcare have seen a growing demand due to the great potential of relieving medical practitioners from routine jobs. In this paper, we investigate the development of an optimization-based control framework for an ultrasound-guided assistive robot to perform scoliosis assessment. A conventional procedure for scoliosis assessment with ultrasound imaging typically requires a medical practitioner to slide an ultrasound probe along a patient's back. To automate this type of procedure, we need to consider multiple objectives, such as contact force, position, orientation, energy, posture, etc. To address the aforementioned components, we propose to formulate the control framework design as a quadratic programming problem with each objective weighed by its task priority subject to a set of equality and inequality constraints. In addition, as the robot needs to establish constant contact with the patient during spine scanning, we incorporate variable impedance regulation of the end-effector position and orientation in the control architecture to enhance safety and stability during the physical humanrobot interaction. Wherein, the variable impedance gains are retrieved by learning from the medical expert's demonstrations. The proposed methodology is evaluated by conducting real-world experiments of autonomous scoliosis assessment with a robot manipulator xArm. The effectiveness is verified by the obtained coronal spinal images of both a phantom and a human subject.

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Section: Discussionmentioning

confidence: 99%