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Unscented Particle Filters with Refinement Steps for UAV Pose Tracking

Authors
  • Pessanha Santos, Nuno1, 2
  • Lobo, Victor2
  • Bernardino, Alexandre1
  • 1 University of Lisbon, Av. Rovisco Pais 1, Lisbon, 1049-001, Portugal , Lisbon (Portugal)
  • 2 Portuguese Navy Research Center (CINAV), Escola Naval, Base Naval de Lisboa, Almada, 2810-001, Portugal , Almada (Portugal)
Type
Published Article
Journal
Journal of Intelligent & Robotic Systems
Publisher
Springer-Verlag
Publication Date
Jun 01, 2021
Volume
102
Issue
2
Identifiers
DOI: 10.1007/s10846-021-01409-y
Source
Springer Nature
Keywords
License
Yellow

Abstract

Particle Filters (PFs) have been successfully employed for monocular 3D model-based tracking of rigid objects. However, these filters depend on the computation of importance weighs that use sub-optimal approximations to the likelihood function. In this paper, we propose to enrich the filter with additional refinement steps to abridge its sub-optimality. We test the proposed approach in two different types of PFs: (i) an Unscented Particle Filter (UPF), and (ii) the recently proposed Unscented Bingham Filter (UBiF). These filters are applied to the outdoor tracking of a fixed-wing Unmanned Aerial Vehicle (UAV) autonomous landing in a Fast Patrol Boat (FPB), tested in a simulated environment with a real sky gradient filled with clouds. The use of the refinement steps significantly improves the overall accuracy of the method.

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