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Invited Speakers in ICRA 2017 workshop C4 Surgical Robots: Compliant, Continuum, Cognitive, and Collaborative

ICRA 2017 workshop C4 Surgical Robots: 2 June 2017, Friday, Full day, 8:30 to 18:00, Sands Expo and Convention Centre, Marina Bay Sands, Singapore

Robert D. Howe, Harvard University

Continuum - Enabling Autonomous Ultrasound-based Procedure Guidance In Cardiac Interventions

Abstract: Robotic cardiac catheterization using ultrasound (US) imaging catheters provides real-time imaging from within the heart while reducing the difficulty in manually steering a four degree-of-freedom (4-DOF) catheter. Accurate robotic catheter navigation in the heart is challenging due to a variety of disturbances including cyclical physiological motions, such as respiration. This paper describes a robotic system that can accurately and robustly steer 4-DOF cardiac catheters and other flexible manipulators despite these disturbances. The performance of the system is demonstrated in a vasculature phantom and an in vivo porcine animal model. Accurately tracking moving structures can improve intra-procedural treatment and visualization.

Robert D. Howe is Abbott and James Lawrence Professor of Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences. Professor Howe founded the BioRobotics Laboratory in 1990, which investigates the roles of sensing and mechanical design in motor control, both in humans and in robots. His research interests focus on robot and human manipulation and the sense of touch. Biomedical applications of this work include the development of robotic and image-guided approaches to minimally invasive surgical procedures. Dr. Howe earned a bachelors degree in physics from Reed College, then worked as a design engineer in the electronics industry in Silicon Valley. He received a doctoral degree in mechanical engineering from Stanford University in 1990, and then joined the faculty at Harvard.

Robert J. Webster III, Vanderbilt University

Continuum - Single Port Robots as Hand-Held Tools … and When to do the Opposite

Abstract: Advancements in design and user interfaces have recently enabled hand-held single port robots. Made by delivering needle-sized continuum robots through clinical endoscopes, these robots assist in laser-based surgeries in small anatomical spaces. This talk will discuss transurethral prostate surgery and neurosurgery as examples where this capability is beneficial. But sometimes the opposite (i.e. a many port, teleoperated system) can be even better, provided each port is itself needle-sized. This talk will also discuss a new concept for parallel continuum robots that are assembled and reconfigured inside the patient during surgery in closed-chest lung interventions.

Robert J. Webster III received the B.S. degree in electrical engineering from Clemson University, Clemson, SC, USA, in 2002, and the M.S. and Ph.D. degrees in mechanical engineering from The Johns Hopkins University, Baltimore, MD, USA, in 2004 and 2007, respectively. In 2008, he joined the Faculty of Vanderbilt University. He is currently an Associate Professor of Mechanical Engineering, Electrical Engineering, Otolaryngology, Neurological Surgery, and Urologic Surgery, and directs the Medical Engineering and Discovery Laboratory. He serves on the steering committee for the Vanderbilt Institute in Surgery and Engineering, which brings together physicians and engineers to solve challenging clinical problems. He is the Chair of the SPIE Image-Guided Procedures, Robotic Interventions, and Modeling Conference, and is an Associate Editor for IEEE TRANSACTIONS ON ROBOTICS. His research interests include surgical robotics, image-guided surgery, and continuum robotics. Dr. Webster received the IEEE Robotics & Automation Society Early Career Award, the National Science Foundation CAREER award, the Robotics Science and Systems Early Career Spotlight Award, and the IEEE Volz Award.

Paolo Fiorini, University of Verona

Cognitive - Surgical data analysis: training and skill assessment

Abstract: The availability of the da Vinci Research Kit (DVRK) has prompted the development of realistic tests to assess the quality of the performed tasks and, consequently, the operator skills. However, the data available are limited to the JIGSAW data set and do not cover most of the aspects of skill learning. In this talk we will present the initial analysis of data generated by medical students carrying simple tasks with the DVRK and a training simulator, and performing more complex micro anastomosis tasks. We have structured the data for easier processing and we have applied performance measurements to compare the effectiveness of simulator training, for simpler task, and of extended practice for the more complex tasks. We show that the data analysis gives clear indication of the subject skills and permits to extract some insight into the process followed by the students to carry out the tasks.

Paolo Fiorini, received the Laurea degree in Electronic Engineering from the University of Padova, (Italy), the MSEE from the University of California at Irvine (USA), and the Ph.D. in ME from UCLA (USA). From 1985 to 2000, he was with NASA Jet Propulsion Laboratory, California Institute of Technology, where he worked on autonomous and teleoperated systems for space experiments and exploration. In 2001 returned to Italy at the School of Science of the University of Verona (Italy) where is a Full Professor of Computer Science. His research focuses on teleoperation for surgery, space, service and exploration robotics, and autonomous navigation of robots and vehicles. In 2001 he founded the ALTAIR robotics laboratory, which has been awarded several EU and Italian grants, including projects on robotic surgery, such as Accurobas, Safros, Isur, and Eurosurge. In 2009, he founded the company Surgica Robotica for the development of a new surgical robot for abdominal surgery that received the CE certification in 2012. He is an IEEE Fellow (USA, 2009), Corresponding Member of the Academy of Agriculture, Sciences and Letters (Verona, 2015), and Honorary Professor of Obuda University (Budapest, 2016).

Jaydev P. Desai, Georgia Institute of Technology

Continuum & Cognitive - Flexible robots for minimally invasive surgical procedures

Abstract: This talk will focus on our work in the area of flexible meso-scale robotic systems for neurosurgery as well as our recent efforts in developing steerable guidewire technology for intravascular interventions. In the area of neurosurgery, we are focusing on developing flexible 3-D printed minimally invasive neurosurgical intracranial robot (MINIR-II), that is patient-specific and disposable. It is equipped with electrocautery and suction and irrigation capabilities to electrocauterize and aspirate deep-seated brain tumor. The robot has three segments, the stiffness of which can be independently modulated to improve its maneuverability. An MRI-compatible remote actuation setup with a quick connect module has been developed for the robot. Another meso-scale robot for neurosurgical intracerebral hemorrhage evacuation (NICHE) has also been developed based on smart actuators made of shape memory alloy. By integrating the motion of a torsion joint with a distal bending tip, the end effector of the robot can articulate within the hemorrhage cavity for effective treatment. Additionally, a lightweight skull-mounted headframe is developed to precisely align the NICHE robot with a planned trajectory towards the target. Finally, in the area of intravascular intervention, we have developed a micro-scale mechanically actuated robotic guidewire with the goal of allowing a clinician access through arterial sections that are hard to navigate, such as in peripheral artery disease procedures (PAD). The guidewire prototype is constructed from a single Nitinol tube by laser cutting asymmetric bi-directional notches to achieve multiple degrees-of-freedom. This steerable Nitinol tube has an outer diameter of 0.78 mm (< 2.4 Fr)!

Dr. Jaydev P. Desai is currently a BME Distinguished Faculty Fellow in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology (GIT). Before joining GIT He served as Professor in the Department of Mechanical Engineering and a Member of the Maryland Robotics Center at the University of Maryland, College Park (UMCP). Prior to joining UMCP, he was an Associate Professor at Drexel University. He completed his undergraduate studies from the Indian Institute of Technology, Bombay, India, in 1993. He received his M.A. in Mathematics in 1997, M.S. and Ph.D. in Mechanical Engineering and Applied Mechanics in 1995 and 1998 respectively, all from the University of Pennsylvania. Prior to joining Drexel University, he was a Post-Doctoral Fellow in the Division of Engineering and Applied Sciences at Harvard University. He is a recipient several NIH R01 awards, NSF CAREER award, and was also the lead inventor on the “Outstanding Invention of 2007 in Physical Science Category” at the University of Maryland, College Park. He is also the recipient of the Ralph R. Teetor Educational Award. In 2011, he was an invited speaker at the National Academy of Sciences “Distinctive Voices” seminar series on the topic of “Robot-Assisted Neurosurgery” at the Beckman Center. He was also invited to attend the National Academy of Engineering’s 2011 U.S. Frontiers of Engineering Symposium. His research interests include image-guided surgical robotics, reality-based soft-tissue modeling for surgical simulation, grasping, haptics, and micro-scale cell and tissue characterization. He is also a member of the ASME and IEEE.

Elena De Momi, Politecnico di Milano

Collaborative interfaces for human robot interaction

Abstract: It is acknowledged that tele-operated robots can provide useful assistance in case of delicate or dangerous operations, remotely performed by the human operator, such as plants decommissioning or surgical tasks. The task execution Performances could be increased by 1) improving the hardware design and the control of tele-operator (master) interfaces 2) providing ad adaptive assistance to allow smoothening the control sharing between the robot and the human. The talk is aimed at showing the researchers of Politecnico di Milano towards the understanding of the learning and motor control aspects involved in human robot collaboration in order to offer solutions that would eventually improve the interaction between the robot and the human operator.

Elena De Momi, MSc in Biomedical Engineering in 2002, PhD in Bioengineering in 2006, currently Assistant Professor in Electronic Information and Bioengineering Department (DEIB) of Politecnico di Milano. She was co-founder of the Neuroengineering and Medical Robotics Laboratory, in 2008, being responsible of the Medical Robotics section. She has been an Associate Editor of the Journal of Medical Robotics Research and of the International Journal of Advanced Robotic Systems. In 2016 she has been an Associated Editor of the IEEE International Conference on Robotics and Automation. Her academic interests include image-processing, virtual environments, augmented reality and simulators, teleoperation, haptics, medical robotics, neuromechanics. She participated to several EU funded projects in the field of Surgical Robotics (ROBOCAST, ACTIVE and EuRoSurge, where she was PI for partner POLIM). She is currently PI for POLIMI of the EDEN2020 project, aimed at developing a neurosurgery drug delivery system. She has been evaluator and reviewer for the European Commission in FP6 and FP7.

Pietro Valdastri, University of Leeds

Compliant and Cognitive - Lifesaving Capsule Robots

Abstract: The talk will focus on Medical Capsule Robots. Capsule robots are cm-size devices that leverage extreme miniaturization to access and operate in environments that are out of reach for larger robots. In medicine, capsule robots can be designed to be swallowed like a pill and to diagnose and treat mortal diseases, such as cancer. The talk will move from capsule robots for the inspection of the digestive tract toward a new generation of surgical robots and devices, having a relevant reduction in size and invasiveness as the main driver for innovation. During the talk, we will discuss the recent enabling technologies that are being developed at the University of Leeds to transform medical robotics. These technologies include magnetic manipulation of capsule robots, water jet propulsion, real-time tracking of capsule position and orientation, magnetic force measurement, miniature mechatronic design, small-scale electronic circuits, and open-source design environments.

Prof. Valdastri’s academic career started with a Laurea degree cum Laude in Electronic Engineering from the University of Pisa in 2001 and a PhD degree cum Laude in Biomedical Engineering from Scuola Superiore Sant’Anna in 2006, with Prof. Paolo Dario as primary advisor. After the PhD, he served as Assistant Professor of Biomedical Engineering at the BioRobotics Institute of Scuola Superiore Sant’Anna for three years, focusing on implantable medical devices and surgical robotics. In 2011, Prof. Valdastri moved to Vanderbilt University, where he became Assistant Professor of Mechanical Engineering, with secondary appointments in the Electrical Engineering Department and in the Division of Gastroenterology, Hepatology and Nutrition of the Vanderbilt University Medical Center. At Vanderbilt University, Prof. Valdastri founded the Science and Technologies Of Robotics in Medicine (STORM) Lab (, a research lab focusing on medical capsule robots for gastrointestinal endoscopy and abdominal surgery. In 2016, he moved to Leeds as Chair in Robotics and Autonomous Systems with a primary appointment in the School of Electronic and Electrical Engineering and a secondary appointment in the School of Mechanical Engineering. In Leeds, Prof. Valdastri is directing the Institute of Robotics, Autonomous System and Sensing (IRASS) and the STORM Lab. Prof. Valdastri is a Royal Society Wolfson Research Merit Award holder, a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), one of the Editors of the IEEE International Conference on Robotics and Automation, a member of the Technology Committee of the European Association for Endoscopic Surgery (EAES), and a member of the steering committee of the International Society for Medical Innovation and Technology (iSMIT). To date, STORM Lab’s research has been featured by several tech magazines, including WIRED, IEEE Spectrum, Medgadget, Medical Design Technology Magazine, Medical Xpress, Newswise, NSF Science Now.

Katherine J. Kuchenbecker, University of Pennsylvania & Max Planck Institute

Cognitive - Physical Instrument Interactions Strongly Relate to Robotic Surgical Skill

Abstract: Clinical robotic surgery systems do not currently provide haptic feedback because surgical instrument interactions are difficult to measure and display. Several years ago, my team invented a way to use accelerometers and voice-coil actuators to allow surgeons to feel and/or hear the high-frequency vibrations of robotic instruments as they interact with patient tissue and other tools. Surgeons strongly prefer the addition of these tactile cues, and the necessary vibration signals occur continually during real operations. Watching videos of both expert and novice robotic surgeons showed us that the operator’s technical skill dictates the quality of their instrument interactions, with better surgeons being faster, more gentle, and more coordinated (lower tool vibrations). By analyzing recorded force, acceleration, and time data, we then created a set of machine learning algorithms that can rate previously unseen trials of peg transfer on the GEARS inventory with a reliability that is comparable to human raters. Finally, we recently demonstrated that allowing a trainee to feel the magnitude of the force they are exerting with the robot (through tactile wrist-squeezing devices) drastically reduces their applied forces both during and after the trials where they receive this feedback.

Katherine J. Kuchenbecker received the PhD degree in Mechanical Engineering from Stanford University in California, USA, in 2006. After a postdoctoral research fellowship at the John Hopkins University in Baltimore she became an Assistant Professor in the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania in Philadelphia. She was tenured and promoted to Associate Professor in 2013, when she also received a secondary appointment in the Penn Department of Computer and Information Science. Since June 2016 she has been Director and Scientific Member at the Max Planck Institute for Intelligent Systems in Stuttgart. Prof. Kuchenbecker received the 2009 National Science Foundation CAREER Award and the 2012 IEEE Robotics and Automation Society Academic Early Career Award. She is cochairing the IEEE Haptics Symposium in 2016 and 2018, and she is presently a co-chair of the IEEE RAS Technical Committee on Haptics.

Ilana Nisky, Ben-Gurion University of the Negev

Cognitive and collaborative - Human sensorimotor control for evaluating the skill of surgeons and the transparency of teleoperation in surgical robotics

Abstract: Robotic manipulators are widely used in a variety of medical applications, including robot-assisted minimally-invasive surgery (RAMIS). Robotic devices are also used to study the human sensorimotor system, and their use has led to the development of rigorous computational models and theories of human motor control. However, the design and control of surgical robots is rarely informed by these models and theories, thus impeding the realization of surgical robots’ full potential. For example, even though surgeons rely strongly on their sense of touch during open surgery, state-of-the-art teleoperated robot-assisted surgery systems do not provide them with touch information. This and other current gaps may be closed with human-centered approaches to control and design of medical robots. In this talk, I will discuss our efforts towards understanding the sensorimotor performance of surgeons in robot-assisted surgery. I will present our studies of teleoperated and open tasks performed by experienced robotic surgeons and novices towards modeling of surgeons’ movements. I will also present our studies of human-centered evaluation of the effect of teleoperation control parameters on transparency of RAMIS by characterizing human perception and action in teleoperated grasping. These studies are part of a research framework that applies neuroscience to solve challenging problems in medical robotics, studies users interacting with medical robots to advance neuroscience, and strives to employ both to improve the quality of life for patients.

Ilana Nisky received the B.Sc (summa cum laude), M.Sc. (summa cum laude), and Ph.D. in Biomedical Engineering from the Department of Biomedical Engineering, Ben-Gurion University of the Negev, Israel, in 2006, 2009, and 2011, respectively. She is currently a senior lecturer in the Department of Biomedical Engineering, Ben-Gurion University of the Negev, where she is the head of the Biomedical Robotics Lab. She was previously a postdoctoral research fellow in the Department of Mechanical Engineering, Stanford University. Her research interests include human motor control, haptics, robotics, human and machine learning, teleoperation, and robot-assisted surgery. She is a member of the BGU ABC Robotics Initiatuve and serves on the steering committee of the Zlotowski Center for Neuroscience. She is a member of IEEE, the Society for the Neural Control of Movement, the Society for Neuroscience, Technical Committee on Haptics, and an Executive Committee member of the Eurohaptics Society.

Wen P. Liu, Intuitive Surgical

Title: Between the C’s - Image Guidance in Robotic-Assisted Surgery

Abstract: Robotic-assisted surgery requires intraoperative precision and three-dimensional spatial understanding of the surgical target and its surrounding anatomy. Although the magnification and stereo capabilities of current robotic-assisted surgery provide high-resolution rendering of the surgical field, tactile feedback is diminished or absent due to tele-manipulation, which increases the surgeon’s reliance on visual cues. Furthermore, a loss of orientation or localization adds to the inherent risks of breaching critical structures, especially in the hands of inexperienced surgeons. Thus for robotic-assisted surgery the integration of medical images be invaluable in providing information regarding anatomic structures beyond human sight. Image guidance objectives include planning traversals for target resection, margin delineation, and reconstruction while controlling or preserving critical functional structures. This presentation focuses on the integration of models from preoperative imaging as well as highlights of research adapting various modalities of medical imaging techniques for intraoperative needs in robotic-assisted surgery.

Wen P. Liu, prior to the completion of her Computer Science PhD in 2014 at Johns Hopkins University, Wen P. Liu had completed a bachelor’s degree in Berkeley and a master’s at Stanford. Her PhD research in image-guided surgery was advised by Dr. Russell Taylor and sponsored by Intuitive Surgical Inc (ISI). She has worked at NASA and Siemens Corporate Research prior to her current role in applied research at ISI. She remains passionate about learning and conducting research in medical imaging and image-guided robotics.

Arianna Menciassi, Scuola Superiore Sant’Anna

Compliant and Cognitive - Minimally Invasive Surgery: From Soft Surgical Tools to Flexible Platforms for Focused Ultrasounds

Abstract: In this talk, the speaker will introduce the potential of soft surgical instrumentation for improving the flexibility of surgical robotic platform, by accessing areas which are not reached by traditional architectures. This approach can contribute in a dramatic way to reduce the invasiveness of surgery and therapy and to allow internal flexibility without the need of multiple access ports through the patient abdomen. In parallel, another trend of minimally invasive therapy consists of delivering the therapeutic actions by using “disappearing” tools and needles. This is the case of focused ultrasound therapy, which allows to deliver energy to the target area inside the patient without any injury for the tissues in between. Achieving accuracy in targeting, also on moving organs and under US imaging, requires cognitive architectures where the energy beam can track the target and deliver the therapy in a semi-autonomous way.

Arianna Menciassi obtained the M.Sc. in Physics from the University of Pisa in 1995 (magna cum Laude) and the Ph.D. in Bioengineering from the Scuola Superiore Sant’Anna (SSSA) in 1999. In the year 2000 she started her academic career at the SSSA with an untenured position of Assistant Professor of Biomedical Robotics and she became Associate Professor of Industrial Bioengineering in 2006, in the same institution. Currently, she is with The BioRobotics Institute of the SSSA where she is Area Leader of “Surgical Robotics”. Prof. Menciassi teaches at the Scuola Superiore Sant’Anna and the Pisa University (Master Degree in Biomedical Engineering). She carries on an intense research and training activity at high level (master candidates in biomedical engineering, PhD students, etc.). She is normally tutor of more than 15 students. Her main research interests involve biomedical robotics, microsystem technology, nanotechnology and micromechatronics, with a special attention to the synergy between robot-assisted therapy and nanotechnology-related solutions. She carries on an important activity of scientific management of several projects, European and extra-European, thus implying many collaborations abroad. She is co-author of more than 200 scientific publications (more than 120 on ISI journals) and 6 book chapters on biomedical robots/devices and microtechnology. She is also inventor of 25 patents, national and international. She serves in the Editorial Board of the IEEE-ASME Trans. on Mechatronics; she is Co-Chair of the IEEE Technical Committee on Surgical Robotics. In the year 2007, she received the Well-tech Award (Milan, Italy) for her researches on endoscopic capsules, and she was awarded by the Tuscany Region with the Gonfalone D’Argento, as one of the best 10 young talents of the region. From the year 2007, she has been collaborating with the Italian Institute of Technology in Genova, and from April 2010 she is affiliated member of the Center for MicroBioRobotics of IIT@SSSA (

Ken Goldberg, UC Berkeley

Title: Cognitive - Bootstrapping Deep Reinforcement Learning of Surgical Tensioning with An Analytic Model

Abstract: Deformable materials are most effectively cut when held in tension, and the optimal direction and magnitude of tension changes as the more of the material is cut. In prior work, we designed a tensioning planner using Trust Region Policy Optimization (TRPO) over a finite-element model to simulate the effect of different tensions and find a tensioning policy to assist a given cutting trajectory. However, scaling this method to higher resolution models and multiple tensioning arms results in a prohibitive sample complexity. This workshop paper explores the feasibility of reducing the sample-complexity of TRPO by initializing training with a simplified analytical model based on Hooke’s Law. Our initial results suggest that the analytic model is within 25% of the final reward of TRPO achieves on three different cutting trajectories, but runs two orders of magnitude faster. This allows TRPO to scale to simultaneously plan for 2,3, and 4 tensioning arms.

Ken Goldberg is an artist, inventor, and UC Berkeley Professor. He is Chair of the Industrial Engineering and Operations Research Department, with secondary appointments in EECS, Art Practice, the School of Information, and Radiation Oncology at the UCSF Medical School. Ken is Director of the CITRIS “People and Robots” Initiative and the UC Berkeley AUTOLAB where he and his students pursue research in geometric algorithms and machine learning for robotics and automation in surgery, manufacturing, and other applications. Ken developed the first provably complete algorithms for part feeding and part fixturing and the first robot on the Internet. Despite agonizingly slow progress, Ken persists in trying to make robots less clumsy. He has over 200 peer-reviewed publications and eight U.S. Patents. He co-founded and served as Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering. Ken's artwork has appeared in 70 exhibits including the Whitney Biennial and films he has co-written have been selected for Sundance and nominated for an Emmy Award. Ken was awarded the NSF PECASE (Presidential Faculty Fellowship) from President Bill Clinton in 1995, elected IEEE Fellow in 2005 and selected by the IEEE Robotics and Automation Society for the George Saridis Leadership Award in 2016.

Tim Salcudean, University of British Columbia

Title: Cognitive - Ultrasound-based Guidance for Robot-assisted Prostate Surgery

Abstract: We present our approaches to integrating ultrasound and magnetic resonance imaging with the da Vinci medical robotic system for prostate surgery. We will summarize our system design and our calibration and registration techniques and our experience from a first patient study in which this system was used.

Septimiu (Tim) E. Salcudean received his BEng and MEng from McGill University and his PhD from the University of California, Berkeley, all in electrical engineering. From 1986 to 1989, he was a Research Staff Member in the robotics group at the IBM T.J. Watson Research Center. He then joined the Department of Electrical and Computer Engineering at the University of British Columbia, where he holds the Laszlo Chair in Biomedical Engineering and a Canada Research Chair. In 1996 Dr. Salcudean held a Killam Research Fellowship and spent one year at ONERA in Toulouse, France. In 2005 he was on a sabbatical visit at CNRS/TIMG/GMCAO in Grenoble, with Dr. Jocelyne Troccaz. Dr. Salcudean has been a co-organizer of the Haptics Symposium from 2000 - 2002, of a Haptics, Virtual Reality, and Human Computer Interaction Workshop at the Institute for Mathematics and its Applications, and a Technical Editor(1992 - 1994) and Senior Editor (1994 - 2000) of the IEEE Transactions on Robotics and Automation.

Kaspar Althoefer, Queen Mary University of London

Title: Compliant & Continuum: Flexible robots of controllable stiffness for minimally invasive surgery: the STIFF-FLOP project

Abstract: Modern surgical robotic systems such as the da Vinci® Surgical System have been employed to conduct minimally invasive or keyhole surgery. Despite a number of notable advances over current laparoscopic methods, such as reduced training time for the surgeons, ease of use of the robotised system and improved ergonomics for the surgeons, such robot-assisted surgical systems continue to make use of rigid instruments severely restricting the areas they can reach during operations.

Departing from these types of robots, which are fundamentally based on a structure composed of rigid link elements connected via joints, the EU project STIFF-FLOP (STIFFness controllable Flexible and Learnable manipulator for surgical OPerations) has created soft multiple-segment manipulators with controllable stiffness. I will highlight the conceptual ideas behind the project, report on our achievements and how these relate to safety considerations in the context of Robot-assisted Minimally Invasive Surgery (RMIS). Challenges emerging when departing from traditionally rigid instruments and progressing towards flexible and even stiffness-controllable surgical tools will be outlined.

Professor Kaspar Althoefer is an electronics engineer, leading research on Robotics at Queen Mary University of London. After graduating with a degree in Electronic Engineering from the University of Technology Aachen, Germany, and obtaining a PhD in Robot Motion Planning from Kings College London, he joined the Kings Robotics Group in 1996 as a Lecturer. Made a Senior Lecturer in 2006, he was promoted to Reader and Professor in 2009 and 2011, respectively. In April 2016, he joined Queen Mary as full Professor of Robotics Engineering.

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