@article{3400cc2b414b4473b631bc27314d6f65,
title = "Intrinsically compliant parallel robot for fractured femur reduction: Mechanism optimization and control",
abstract = "A robotic system for the reduction of fractured femur bone is proposed in this research to help orthopedics during the labor intensive bone reduction procedures and also save them from radiation stimulated environment. Fractured femur reduction is a good candidate for robotics application owing to its elongated anatomy and strong counteracting forces from surrounding muscles. However, the robot forces should be compliant, and motions need to be accurate. Aiming to achieve these two conflicting objective, a parallel robot actuated by six intrinsically compliant actuators is being proposed here. After an initial design analysis, three performance metrics, namely, the conditioning index, actuator force index and interaction compliance index were identified and formulated. An evolutionary algorithm SPEA2 was employed to simultaneously optimize these objectives by varying the key robot design variables. Subsequent to the optimization, an optimal robot design is obtained which provides the best trade-off between the performance measures. Initial proof of concept experiments were carried out whereby the robot was tested for trajectory following accuracies while maneuvering the moving platform about the three axes. A fuzzy based closed loop feedback controller was implemented on the robot. Excellent trajectory tracking results were observed in response to the sinusoidal inputs.",
keywords = "Fracture, Surgical robot, Control Systems, Femur, Compliant actuation, Robot control, Fracture reduction, Optimization, Parallel robot",
author = "Jamwal, {Prashant K.} and Shahid Hussain and Ghayesh, {Mergen H.}",
note = "Funding Information: This work was supported by FDCR Grant ( 021220FD0251 ) “Robot for Advanced Long Bone Fracture Reduction (R.ALFRED)”. This work was also supported in part by the Human-Centred Technology Research Center, University of Canberra Australia . Funding Information: Prashant K. Jamwal (M{\textquoteright}15 SM{\textquoteright}20) earned Ph.D. degree and a post-doctoral fellowship from the University of Auckland, New Zealand. Earlier he graduated from I.I.T., India, securing first position in all the disciplines. Presently, Prof. Jamwal is working at the school of engineering and design sciences, Nazarbayev University, Nur-Sultan, Kazakhstan. He is actively pursuing research in Artificial Intelligence, multi-objective evolutionary optimization, Bio-mechatronics, and robotics. He has developed medical robots for rehabilitation and surgical applications besides the development of improved algorithms for cancer data analytics. Prof. Jamwal is a member of many IEEE societies including the robotics and automation society. Besides editorial and publishing work, he has won many awards such as best paper awards, best digital solution award for his medical robots, Asian Universities Alliance (AUA) Scholars Award, etc. Recently, United Nations acknowledged one of his robotics projects as one of the top twenty innovative projects in the world. Prof. Jamwal led many government funded research projects including a prestigious World Bank grant. Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",
year = "2021",
month = jul,
doi = "10.1016/j.robot.2021.103787",
language = "English",
volume = "141",
pages = "1--13",
journal = "Robotics and Autonomous Systems",
issn = "0921-8890",
publisher = "Elsevier",
}