DTC Leading Edge Seminar Series
Using a Kinetic Model of Human Gait in Personal Navigation Systems
Aerospace Engineering and Mechanics
College of Science and Engineering
University of Minnesota
Wednesday, October 27, 2010
3:30 p.m. reception
4:00 p.m. seminar
401/402 Walter Library
A kinetic model of human gait developed and its use as a virtual sensor in a dead reckoning system for personal navigation is discussed. The kinetic model developed provides a real-time estimate of stride length and, therefore, can be used to augment other dead reckoning schemes used in personal navigation such as step counting or shoe-mounted Inertial Navigation Systems. Using simulations and experimental data, it is shown that using the kinetic model with a single-axis (scalar) acceleration measurement stride length can be estimated in-situ for straight forward walking. Furthermore, the combination of this approach yields a navigation solution of comparable or better performance to a simple step counting approach. The derivation of this model is discussed in detail and experimental results validating its performance are presented.
Professor Gebre-Egziabher's area of research is in navigation, guidance and control of aerospace vehicles. A particular focus of his research is the application of estimation theory to the development of algorithms and design methodologies to optimally fuse the information from multiple sensors and systems. One of the challenges encountered when dealing with such problems for aerospace applications or other safety and liability critical operations is being able to precisely quantify (in statistical terms) the level of reliability of the algorithms and systems. Examples of engineering applications for his work are in the development of attitude determination systems for satellites, high accuracy navigation of aircraft and evaluating operations of small autonomous aerial vehicles in the national airspace system.
DTC Professer Tian He named 2018 ACM Fellow
Professor Tian He has been named a 2018 Association for Computing Machinery (ACM) Fellow. He has been selected his contributions to wireless networks, sensing systems, and Internet of Things (IoT), areas in which he has made many influential and landmark contributions. More on Tian He.
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