The Human Odometer was a wearable personal localization system for first responders and warfighters. The key idea is that real-time pose and activity information for each member of a team provides enhanced situational awareness for command and control. Bluetooth accelerometers and gyroscopes integrated into a suit tracked a person’s steps and orientation. This information was reported to a battalion commander through a handheld PDA which brought up context-sensitive mapping and position information. My undergraduate senior thesis investigated Kalman filtering to fuse intermittent IMU, GPS, and pedometry data for more accurate positioning as well as learning parameters and variances of the step-detection model.
