RT Journal Article
SR Electronic
T1 Robust GPS-Vision Localization via Integrity-Driven Landmark Attention
JF NAVIGATION: Journal of the Institute of Navigation
JO NAVIGATION
FD Institute of Navigation
SP navi.501
DO 10.33012/navi.501
VO 69
IS 1
A1 Sriramya Bhamidipati,
A1 Grace Gao
YR 2022
UL https://navi.ion.org/content/69/1/navi.501.abstract
AB For robust GPS-vision navigation in urban areas, we propose an integrity-driven landmark attention (ILA) technique via stochastic reachability. Inspired by cognitive attention in humans, we perform convex optimization to select a subset of landmarks from GPS and vision measurements that maximizes integrity-driven performance. Given known measurement error bounds in non-faulty conditions, our ILA technique follows a unified approach to address both GPS and vision faults and is compatible with any off-the-shelf estimator. We analyze measurement deviation to estimate the stochastic reachable set of positions associated with each landmark, which is parameterized via probabilistic zonotope (p-zonotope). We apply set union to formulate a p-zonotopic cost that represents the size of position bounds based on landmark inclusion/exclusion. We jointly minimize the p-zonotopic cost and maximize the number of landmarks via convex relaxation. For an urban data set, we demonstrate improved localization accuracy and robust predicted availability for a pre-defined risk and alert limit.