State estimation for systems with implicit outputs for the integration of vision and inertial sensors

• Type: Article in International Conference Proceedings Book
• Date: 2005

Authors

Pedro Aguiar, AP (Author) Other; Joao P Hespanha (Author) Other

Conference proceedings International

Title: IEEE Conference on Decision and Control

Pages: 621-626

44th IEEE Conference on Decision Control/European Control Conference (CCD-ECC)

Seville, SPAIN, DEC 12-15, 2005

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 6 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-000-6Z8

DOI: 10.1109/cdc.2005.1582225

Abstract (EN): This paper addresses the state estimation of a system with implicit outputs. We formulate the problem in the so-called deterministic H. filtering setting by computing the value of the state that minimizes the induced L-2-gain from disturbances to estimation error, while remaining compatible with the past observations. To avoid weighting the distant past as much as the present, a forgetting factor is also introduced. We show that, under appropriate observability assumptions, the optimal estimate converges globally asymptotically to the true value of the state in the absence of noise and disturbance. In the presence of noise, the estimate converges to a neighborhood of the true value of the state. We apply these results to the estimation of position and attitude of an autonomous vehicle using measurements from an inertial measurement unit (IMU) and a monocular charged-coupled-device (CCD) camera attached to the vehicle.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6