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.