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The purpose of this paper is to present a methodology for medical robot kinematics design developed using a knowledge‐management approach.

A classification of medical robots is proposed based on their kinematic characteristics and 76 robot specifications were collected in a catalogue. Then, having drawn a generic specifications sheet, rules were proposed to choose a structure from these specifications.

Findings are situated at several levels: the catalogue, the classification of robots with respect to their kinematic characteristics, a generic and specific specifications sheet, and an organigram to choose the most relevant structure from the specifications.

This structural synthesis represents a preliminary step in the design of medical robots which will be completed by an additional dimensional synthesis.

This work offers a new methodology for medical robots design distinct from what is usually done for medical or industrial robots design using intuition, expertise and non‐formal knowledge.

This paper aims to present a prototype of medical transportation robot whose positioning accuracy can reach millimeter-level in terms of patient transportation. By using this kind of mobile robot, a fully automatic image diagnosis process among independent CT/PET devices and the image fusion can be achieved.

Following a short introduction, a large-load 4WD-4WS (four-wheel driving and four-wheel steering) mobile robot for carrying patient among multiple medical imaging equipments is developed. At the same time, a specially designed bedplate with self-locking function is also introduced. For further improving the positioning accuracy, the authors proposed a calibration method based on Gaussian process regression (GPR) to process the measuring data of the sensors. The performance of this robot is verified by the calibration experiment and Image fusion experiment. Finally, concluding comments are drawn.

By calibrating the robot’s positioning system through the proposed GPR method, one can obtain the accuracy of the robot’s offset distance and deflection angle, which are 0.50 mm and +0.21°, respectively. Independent repeated trials were then set up to verify this result. Subsequent phantom experiment shows the accuracy of image fusion can be accurate within 0.57 mm in the front-rear direction and 0.83 in the left-right direction, respectively, while the clinical experiment shows that the proposed robot can practically realize the transportation of patient and image fusion between multiple imaging diagnosis devices.

The proposed robot offers an economical image fusion solution for medical institutions whose imaging diagnosis system basically comprises independent MRI, CT and PET devices. Also, a fully automatic diagnosis process can be achieved so that the patient’s suffering of getting in and out of the bed and the doctor’s radiation dose can be obviated.

The general bedplate presented in Section 2 that can be mounted on the CT and PET devices and the self-locking mechanism has realized the catching and releasing motion of the patient on different medical devices. They also provide a detailed method regarding patient handling and orientation maintenance, which was hardly mentioned in previous research. By establishing the positioning system between the robot and different medical equipment, a fully automatic diagnosis process can be achieved so that the patient’s suffering of getting in and out of the bed and the doctor’s radiation dose can be obviated.

The GPR-based method proposed in this paper offers a novel method for enhancing the positioning accuracy of the industrial AGV while the transportation robot proposed in this paper also offers a solution for modern imaging fusion diagnosis, which are basically predicated on the conjoint analysis between different kinds of medical devices.

The purpose of this paper is to describe a calibration method developed to improve the accuracy of a six degrees-of-freedom medical robot. The proposed calibration approach aims to enhance the robot’s accuracy in a specific target workspace. A comparison of five observability indices is also done to choose the most appropriate calibration robot configurations.

The calibration method is based on the forward kinematic approach, which uses a nonlinear optimization model. The used experimental data are 84 end-effector positions, which are measured using a laser tracker. The calibration configurations are chosen through an observability analysis, while the validation after calibration is carried out in 336 positions within the target workspace.

Simulations allowed finding the most appropriate observability index for choosing the optimal calibration configurations. They also showed the ability of our calibration model to identify most of the considered robot’s parameters, despite measurement errors. Experimental tests confirmed the simulation findings and showed that the robot’s mean position error is reduced from 3.992 mm before calibration to 0.387 mm after, and the maximum error is reduced from 5.957 to 0.851 mm.

This paper presents a calibration method which makes it possible to accurately identify the kinematic errors for a novel medical robot. In addition, this paper presents a comparison between the five observability indices proposed in the literature. The proposed method might be applied to any industrial or medical robot similar to the robot studied in this paper.

The following article is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD and innovator regarding his pioneering efforts. The paper aims to discuss these issues.

The interviewee is Dr Nabil Simaan, Professor of Mechanical Engineering, Computer Science and Otolaryngology at Vanderbilt University. He is also director of Vanderbilt’s Advanced Robotics and Mechanism Applications Research Laboratory. In this interview, Simaan shares his unique perspective and approaches on his journey of trying to solve real-world problems in the medical robotics area.

Simaan received his BSc, MSc and PhD in mechanical engineering from the Technion – Israel Institute of Technology. He served as Postdoctoral Research Scientist in Computer Science at Johns Hopkins University. In 2005, he joined Columbia University, New York, NY, as an Assistant Professor of Mechanical Engineering until 2010, when he joined Vanderbilt. His current applied research interests include synthesis of novel robotic systems for surgical assistance in confined spaces with applications to minimally invasive surgery of the throat, natural orifice surgery, cochlear implant surgery and dexterous bimanual microsurgery. Theoretical aspects of his research include robot design and kinematics.

Dr Simaan is a leading pioneer on designing robotic systems and mechanisms for medical applications. Examples include technologies for snake robots licensed to Intuitive Surgical; technologies for micro-surgery of the retina, which led to the formation of AURIS Surgical Robotics; the insertable robotic effector platform (IREP) single-port surgery robot that served as the research prototype behind the Titan Medical Inc. Sport (Single Port Orifice Robotic Technology). Simaan received the NSF Career award for young investigators to design new algorithms and robots for safe interaction with the anatomy. He has served as the Editor for IEEE International Conference on Robotics and Automation, Associate Editor for IEEE Transactions on Robotics, Editorial Board Member of Robotica, Area Chair for Robotics Science and Systems and corresponding Co-chair for the IEEE Technical Committee on Surgical Robotics. In January 2020, he was bestowed the award of Institute of Electrical and Electronics Engineers (IEEE) Fellow for Robotics Advancements. At the end of 2020, he was named a top voice in health-care robotics by technology discovery platform InsightMonk and market intelligence firm BIS Research. Simaan holds 15 patents. A producer of human capital, his education goal is to achieve the best possible outcome with every student he works with.

The Japanese robotic industry has been very silent in medical applications. However, changes in this can now be observed. Above all Hitachi, an electric/machinery giant, is trying to rebuild its robotic business by entering the medical robot market.

The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry engineer-turned successful innovator and leader, regarding the challenges of bringing technological discoveries to fruition. The paper aims to discuss these issues.

The interviewee is Gurvinder S. Virk, an experienced internationally renowned technical expert in robotics, control, engineering and computer science who currently serves as the Technical Director for Innovative Technology & Science Limited (InnotecUK); Adjunct Professor for IIT Ropar, India; Guest Professor in Robotics and Autonomous Systems, KTH Royal Institute of Technology, Sweden; and Trustee and Treasurer, CLAWAR Association Ltd., UK (a UK-registered charity with the mission to advance robotics for the public benefit). In this interview, Prof Virk details his technical/commercialization/regulatory experience with international standing to advance robotics and control engineering globally to deliver mass market robot products.

Prof Virk received a first-class BSc in electronic and electrical engineering from the University of Manchester in 1977; a PhD in Control Theory, Imperial College, London, 1982; and a Diploma of Imperial College in 1982. He has served as Lecturer, Senior Lecturer and Professor of Control and Robotics and related fields since 1983 in UK, New Zealand, Germany and Sweden. He has been involved in several spin-out commercial ventures with CFM Consultants, Ambient Energy Systems Ltd., Portech Ltd., Endoenergy Systems Ltd., Endoenergy Sweden AB, CLAWAR Association Ltd. and EAS Ltd. (NZ).

Throughout his 35-year career, Prof Virk (CEng, FIET, FCIBSE, CMath, FIMA, MIEEE) has been a leader and scientific contributor in the fields of intelligent and advanced robotics, control systems theory and applications, assistive robots and mobile robotics, renewable energy systems for building applications and robot safety. He has produced over 350 refereed publications, filed four patents, supervised 16 successful PhD/MPhil students, created and led international research teams, registered several spin-out companies (and a UK-registered charity) and has led many international externally funded projects (total value of approximately €20m). His notable achievements include leading the creation of the first harmonized ISO safety standard (EN ISO 13482) for personal care robots and being invited to be President of the Evaluation Committee of the ARGOS Challenge to invent autonomous ATEX-certified robots for gas and oil production sites. In addition, Prof Virk has been awarded the Freedom of the City of London for services in promoting Information Technology (IT) in schools and is a Freeman of the Worshipful Company of Information Technology. His pioneering and patented research on assistive wearable exoskeletons will soon be available as affordable products for the elderly.

The purpose of this article is to present a “Q&A interview” conducted by Joanne Pransky of the Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry engineer-turned entrepreneur regarding the evolution, commercialization and challenges of bringing a technological invention to market.

The interviewee is Professor Moshe Shoham, Director of the Robotics Laboratory, Department of Mechanical Engineering, Technion, Israel Institute of Technology. Professor Shoham is also the Founder of Mazor Robotics Ltd. and the co-founder of Microbot Medical. As a pioneer of new and developing fields in medical robotics, Shoham describes his major advancements and innovative approaches.

Professor Moshe Shoham has BSc in Aeronautical Engineering, MSc and DSc in Mechanical Engineering from Technion, where he has been teaching for the past nearly 30 years, and is currently the Tamara and Harry Handelsman Academic Chair in the Faculty of Mechanical Engineering. The Technion is renowned for the ingenuity of its graduates, who comprise 70 per cent of Israel’s founders and managers of high-tech industries, making Israel the greatest concentration of high-tech start-up companies anywhere outside of Silicon Valley, California, USA. Along with Technion’s expert faculty, students and facilities, Professor Shoham founded Mazor Robotics in 2001 and co-founded Microbot Medical Ltd. in 2010.

Professor Shoham, a worldwide acclaimed authority in the field of robotics whose life work is dedicated to developing technologies that improve patient care, is the inventor of the first commercially available mechanical guidance system for spine surgery, the Mazor Robotics Renaissance™ Guidance System. He is also the visionary and creator of the unprecedented Microbot ViRob, an Autonomous Advancing Micro Robot, <1 mm in diameter, which has the ability to crawl within cavities/lumens, allowing physicians to target a disease site with exquisite precision. His latest work includes a revolutionary swimming Micro Robot and the new Mazor Renaissance® Brain Surgery. Professor Shoham holds 30 patents and more than a dozen awards, including the recent prestigious 2013 Thomas A. Edison Patent Award and the election into the National Academy of Engineering.

The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.

This paper focusses on two active intrinsically safe medical robots – Hippocrate and DERMAROB – designed by the LIRMM laboratory and manufactured by SINTERS. For both of them, we discuss design and control issues.