ECE 480Design Team 6 Small, Lightweight Speed and Distance Sensor for Skiers and Snowboarders Michael Bekkala Michael Blair Michael Carpenter Matthew Guibord Abhinav Parvataneni Dr. Shanker Balasubramaniam
Objective • Introduction • Design Requirements • Proposed Solution • Testing Results • Conclusions and Accomplishments
Introduction • Living by the numbers • Measuring and interpreting your performance has never been more valuable • Critical to gain a competitive edge • Most devices are based on repetitive motion but don’t apply to skiing or snowboarding • Nike+ • Bicycle speedometer • Goal: Build a speed and distance sensor for skiers and snowboarders
Design Requirements Operable in Subzero Temperatures Accurately record speed and distance Useable in winter apparel Cost – less than $500 Lightweight – Less than two pounds Battery Life greater than 2 hours
Proposed Solution • Integration of two major systems • Global Positioning System (GPS) • Inertial Navigation System (INS)
Inertial Navigation System • Comprised of accelerometers and gyroscopes • Accelerations • Angular Velocities • Requires analog to digital conversion • Careful calibration is required to achieve high accurate readings • Gives great short-termaccuracy, but errors growwith time.
Global Positioning System http://en.wikipedia.org/wiki/Gps • Gives position in terms of longitude, latitude, and altitude • Determine distance, displacement and speed • NMEA 0183 communications standard • Long term reliability, butpoor short term accuracy. • Sampled at 1Hz
Kalman Filtering • Advanced sensor integration technique • Uses statistical error measurements to provide a better estimate • Accuracy improves with time • Can use the estimate to regulate INS errors
User Interface Easily accessible menu displayed on LCD Review Performance Average and Peak Speed (mph) Distance and Displacement (miles) Color changing buttons Color of button changes depending on their use Intuitive color scheme aids usability (ie. Red for Stop, Green for Go)
PC Interface Upload run data from device Can be saved on your PC for performance tracking and reference Points can be plotted in Google Earth Visual representation ofdata using graphs
Successful Failure • Reached beyond design requirements with an innovative solution • Unpredicted complexity of INS and Kalman filter • Hardware implemented, software not ready • Invaluable knowledge gained through: • Research • Trial and error • Despite proposed solution being a successful failure • GPS solution that meets and exceeds design requirements • Extensive user functionality • Store, retrieve, and manage data all on device or through a PC • Higher data sample rate for greater accuracy • Rechargeable battery
Kalman Filter Divergence • Difficult to troubleshoot due to 1200+ lines of code • Unsuccessful in determining cause of divergence • Poor Initialization might be to blame • Confident that with more time, root cause could be determined
Testing Results Several Trials Moving vehicle On foot Varying speeds and distances Peak speed had significant error One bad sample results in erroneous reading Average speed had reasonable accuracy based on number of data points Results verified by digital speedometer and consumer GPS.
Conclusions and Accomplishments • GPS Solution • Accurate average and peak speeds • Distance accurate over a large span • Inaccurate over short spans and slow speeds • Robust Display Menu • Allows easy access to data and configuration options • PC Interfacing • Plot a run on Google Earth with the click of a mouse • Plot speed over time to visualize a run
Future Considerations • Printed Circuit Board • USB Compatibility • Wireless headset communication via Bluetooth • Smaller form factor • INS integrated through Kalman Filtering