Random Set Methods: Estimation of Multiple Extended Objects
2014 (English)In: IEEE robotics & automation magazine, ISSN 1070-9932, Vol. 21, no 2, 73-82 p.Article in journal (Refereed) Published
Random set based methods have provided a rigorous Bayesian framework and have been used extensively in the last decade for point object estimation. In this paper, we emphasize that the same methodology offers an equally powerful approach to estimation of so called extended objects, i.e., objects that result in multiple detections on the sensor side. Building upon the analogy between Bayesian state estimation of a single object and random finite set estimation for multiple objects, we give a tutorial on random set methods with an emphasis on multiple extended object estimation. The capabilities are illustrated on a simple yet insightful real life example with laser range data containing several occlusions.
Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2014. Vol. 21, no 2, 73-82 p.
Control Engineering Signal Processing
IdentifiersURN: urn:nbn:se:liu:diva-105530DOI: 10.1109/MRA.2013.2283185ISI: 000337124700012OAI: oai:DiVA.org:liu-105530DiVA: diva2:708079
FunderLinnaeus research environment CADICS