Image-guided therapy is a clinical procedure under 2-D or 3-D image guidance such as MRI and CT images to accurately deliver surgical devices to diseased or cancerous tissue. This emerging field is interdisciplinary, combining the technology of robotics, computer science, engineering and medicine. Image-guided therapy allows faster, safer and more accurate minimally invasive surgery and diagnosis. In this talk, Dr. Tse will present the technological challenges in the field, followed by his research in MRI-guided therapy for brachytherapy, ablation and stem cell treatment in the prostate, the heart and the spine. These procedures consist of the latest imaging and robotic technology in minimally invasive therapy.
Dr. Zion Tse is an Assistant Professor in the College of Engineering and the Principal Investigator of the Medical Robotics Lab at the University of Georgia. Formerly, he was a visiting scientist in the Center for Interventional Oncology at National Institutes of Health, and a research fellow in the Radiology Department at Harvard Medical School, Brigham and Women’s Hospital. He received his PhD in Medical Robotics from Imperial College London, UK. His academic and professional experience has related to mechatronics, medical devices and surgical robotics. Dr. Tse has designed and prototyped a broad range of novel clinical devices, most of which have been tested in animal and human trials.
Human-controlled robotic systems can greatly improve healthcare by synthesizing information, sharing knowledge with the human operator, and assisting with the delivery of care. This talk will highlight projects related to new technology for surgical simulation and training, as well as a more in depth discussion of a novel teleoperated robotic system that enables complex needle-based medical procedures, currently not possible. The central element to this work is understanding how to integrate the human with the physical system in an intuitive and natural way, and how to leverage the relative strengths between the human and mechatronic system to improve outcomes.
Ann Majewicz completed B.S. degrees in Mechanical Engineering and Electrical Engineering at the University of St. Thomas, the M.S.E. degree in Mechanical Engineering at Johns Hopkins University, and the Ph.D. degree in Mechanical Engineering at Stanford University. Dr. Majewicz joined the Department of Mechanical Engineering as an Assistant Professor in August 2014, where she directs the Human-Enabled Robotic Technology Laboratory. She holds at courtesy appointment in the Department of Surgery at UT Southwestern Medical Center. Her research interests focus on the interface between humans and robotic systems, with an emphasis on improving the delivery of surgical and interventional care, both for the patient and the provider.
The ability to manufacture micro-scale sensors and actuators has inspired the robotics community for over 30 years. There have been huge success stories; MEMS inertial sensors have enabled an entire market of low-cost, small UAVs. However, the promise of ant-scale robots has largely failed. Ants can move high speeds on surfaces from picnic tables to front lawns, but the few legged microrobots that have walked have done so at slow speeds (< 1 body length/sec) on smooth silicon wafers. In addition, the vision of large numbers of microfabricated sensors interacting directly with the environment has suffered in part due to the brittle materials used in microfabrication. This talk will present our progress in the design of sensors, mechanisms, and actuators that utilize new microfabrication processes to incorporate materials with widely varying moduli and functionality to achieve more robustness, dynamic range, and complexity in smaller packages. Results include skins of soft tactile or strain sensors with high dynamic range, new models of bio-inspired jumping mechanisms, and magnetically actuated legged microrobots from 1 gram down to 1 milligram that provide insights into simple design and control for high speed locomotion in small-scale mobile robots.
Sarah Bergbreiter joined the University of Maryland, College Park in 2008 and is currently an Associate Professor of Mechanical Engineering, with a joint appointment in the Institute for Systems Research. She received her B.S.E. degree in Electrical Engineering from Princeton University in 1999, and the M.S. and Ph.D. degrees from the University of California, Berkeley in 2004 and 2007 with a focus on microrobotics. Her research uses inspiration from microsystems and biology to improve robotics performance at all scales. She has been awarded several honors including the DARPA Young Faculty Award in 2008, the NSF CAREER Award in 2011, and the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2013 for her research on engineering robotic systems down to sub-millimeter size scales. She also received the Best Conference Paper Award at IEEE ICRA 2010 on her work incorporating new materials into microrobotics and the NTF Award at IEEE IROS 2011 for early demonstrations of jumping microrobots. She currently serves on DARPA’s Microsystems Exploratory Council and as an associate editor for IEEE Transactions on Robotics and ASME Journal on Mechanisms and Robotics.
This talk will show that attitude Kalman filters can be simple in design while also being robust and accurate despite the highly nonlinear nature of attitude (i. e., orientation) estimation. Three different filters are discussed, all using quaternions and small-angle approximations of attitude errors: an Extended Kalman filter as well as an Unscented Kalman filter for a gyro-based situation, and an Extended Kalman filter for a gyro-less one. In additon to the three-axis attitude, all of the filters also estimate corrections to the angular velocity – random walk modeled biases in the gyro measured case, and first-order Markov modeled corrections in the gyro-less case, which involves angular velocity computed from mass properties and control data.
The filters are evaluated using extensive real and simulated data from low-Earth orbiting NASA satellites such as Tropical Rainfall Measurement Mission, Solar, Anomalous, and Magnetospheric Particle Explorer, Earth Radiation Budget Satellite, Wide Field Infrared Explorer, and Fast Auroral Snapshot Explorer. The evaluations predominantly involve stressing “magnetometer-only” scenarios, i. e., using only a three-axis magnetometer to sense the attitude. Comparisons are made with attitude and rate knowledge obtained using coarse sensors and single-frame algorithms, and also with results from an Unscented Kalman filter with a more complicated attitude pameterization.
Dr. Murty Challa received a B.Sc. in physics from Andhra University, Visakhapatnam, India, and a Ph.D. in physics from the University of Georgia, Athens, Georgia. His professional interests and actvities include: estimation and data fusion algorithms such as Kalman filters, batch estimators, and simultaneous localization and mapping; track correlation/ association; guidance, navigation, and control for spacecraft and unmanned vehicles; missile defense; quantum computing; statistical mechanics; computational physics; solid state physics/ materials science. He is currently a member of the Senior Professional Staff of Johns Hopkins Applied Physics Laboratory (JHU/APL), Maryland, USA. Prior to JHU/APL, he was senior staff at Institute for Defense Analyses, Alexandria, VA, and at Computer Sciences Corporation supporting NASA Goddard Space Flight Center, Greenbelt, MD. Dr. Challa’s academic positions include post-doctoral appointments in physics at Michigan State University and Virginia Commonwealth University, and an adjunct position in physics at George Washington University. He has also served as a consultant to Iridium Satellite, LLC.