Modelling the motion of a sensor attached to a walking person
This paper describes an implemented system to measure and track the motion of a sensor which is attached to a person or walking robot. The complex gait motion undergone by a structure-measuring sensor during walking introduces significant uncertainty into the measurements it takes. By measuring and tracking the sensors motion, more meaningful information can be obtained from the measurements, and predictions can be made about the future observed position of important objects in the world. The use of motion measuring devices is discussed and compared to the possible estimation of motion by the structural sensor itself. Analysis of walker motion is performed through the use of Gabor wavelets and the Extended Kalman Filter. The method tracks and predicts motions reliably while the walker walks in a straight path or turns corners. Particular attention is focussed on the case where the structural sensor is computer vision, and the benefit that a motion model can provide with it.
human gait wearable computing legged robots sensing