Estimation of vehicle pose and road curvature based on Perception-Net

Proposed is an algorithm to estimate vehicle pose and road curvature by geometrically fusing sensor data from camera image, velocity meter, and steering wheel encoder. To achieve computational efficiency in processing in a real time sequence, we propose a method to model the lane on the road as a series of connected rectangular plates. We propose an algorithm, the so called "Perception-Net", where not only variables denoting the vehicle pose and the road curvature, but also the corresponding uncertainties are propagated in forward and backward directions in such a way to satisfy the given constraint condition, maintain consistency, reduce the uncertainties, and guarantee robustness. An experimental result is also presented.