Incremental sensor fusion in factor graphs with unknown delays
Niko Suenderhauf, Sven Lange, Peter Protzel · QUT ePrints (Queensland University of Technology) · 2013
Sensor fusion by incremental smoothing in factor graphs allows the easy incorporation of asynchronous and delayed measurements, which is one of the main advantages of this approach compared to the ubiquitous filtering techniques. While incorporating delayed measurements into the factor graph representation is in principle easy when the delay is known, handling unknown delays is a non-trivial task that has not been explored before in this context. Our paper addresses the problem of performing incremental sensor fusion in factor graphs when some of the sensor information arrive with a significant unknown delay. We develop and compare two techniques to handle such delayed measurements under mild conditions on the characteristics of that delay: We consider the unknown delay to be bounded and quantizable into multiples of the state transition cycle time. The proposed methods are evaluated using a simulation of a dynamic 3-DoF system that fuses odometry and GPS measurements.