Vehicle localization integrity based on trajectory monitoring

For mobile robots to navigate autonomously, knowing with certainty their location is fundamental. However, this is difficult when operating in complex outdoors environments, and often results are inaccurate. To guarantee the certainty of the location estimates, the notion of integrity is used. This is a measure of the degree of confidence that provides a guaranteed location zone. The process consists in removing outliers amongst the measurements using Fault Detection and Exclusion (FDE) algorithms and then to compute Protection Levels (PL) that quantify the integrity zone. This is applicable mainly to Global Navigation Satellite Sytems (GNSS) in the aerospace domain where data redundancy exists and few multipath, which is not the case for land applications. In this paper, a new approach to localization integrity for land mobile robots is proposed by combining vehicle and GNSS data, stored within a short-term memory, the data horizon. This formulation allows for the application of FDE algorithms on the combined data set. It also leads to a gain of redundancy that enables PLs to be reduced and to increase the availability of integrity algorithms.