TY - JOUR
T1 - Ultrasound-Guided Assistive Robots for Scoliosis Assessment With Optimization-Based Control and Variable Impedance
AU - Duan, Anqing
AU - Victorova, Maria
AU - Zhao, Jingyuan
AU - Sun, Yuxiang
AU - Zheng, Yongping
AU - Navarro-Alarcon, David
PY - 2022/7
Y1 - 2022/7
N2 - Assistive robots for healthcare have witnessed a growing demand over the past decades. In this letter, we investigate the development of an optimization-based control framework with variable impedance for an assistive robot to perform ultrasound-guided scoliosis assessment. The conventional procedure for scoliosis assessment using ultrasound imaging typically requires a medical practitioner to slide an ultrasound probe along a patient's back while maintaining a certain magnitude of the contact force. To automate such a procedure, we need to consider multiple objectives, such as contact force, position, orientation, energy, posture, etc. To coordinate different objectives, we propose to formulate the control framework as a quadratic programming problem with each objective weighted by a tunable task priority, subject to a set of equality and inequality constraints. As the procedure requires the robot to establish a constant contact force with the patient during scanning, we incorporate variable impedance regulation of the end-effector to enhance safety and stability during the physical human-robot interaction; The variable impedance gains are then retrieved by learning from medical expert's demonstrations. The proposed methodology is evaluated with a robotic system performing autonomous scoliosis assessment with multiple human subjects involved. The effectiveness of our approach is verified by the coronal spinal images obtained with the robot. © 2022 IEEE.
AB - Assistive robots for healthcare have witnessed a growing demand over the past decades. In this letter, we investigate the development of an optimization-based control framework with variable impedance for an assistive robot to perform ultrasound-guided scoliosis assessment. The conventional procedure for scoliosis assessment using ultrasound imaging typically requires a medical practitioner to slide an ultrasound probe along a patient's back while maintaining a certain magnitude of the contact force. To automate such a procedure, we need to consider multiple objectives, such as contact force, position, orientation, energy, posture, etc. To coordinate different objectives, we propose to formulate the control framework as a quadratic programming problem with each objective weighted by a tunable task priority, subject to a set of equality and inequality constraints. As the procedure requires the robot to establish a constant contact force with the patient during scanning, we incorporate variable impedance regulation of the end-effector to enhance safety and stability during the physical human-robot interaction; The variable impedance gains are then retrieved by learning from medical expert's demonstrations. The proposed methodology is evaluated with a robotic system performing autonomous scoliosis assessment with multiple human subjects involved. The effectiveness of our approach is verified by the coronal spinal images obtained with the robot. © 2022 IEEE.
KW - learning from demonstration
KW - Medical robots and systems
KW - optimization and optimal control
KW - physical human-robot interaction
KW - task and motion planning
UR - http://www.scopus.com/inward/record.url?scp=85133752232&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85133752232&origin=recordpage
U2 - 10.1109/LRA.2022.3186504
DO - 10.1109/LRA.2022.3186504
M3 - RGC 21 - Publication in refereed journal
SN - 2377-3766
VL - 7
SP - 8106
EP - 8113
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 3
ER -