Location Estimation using Delayed Measurements

Martin Bak; Thomas Dall Larsen; Peter Magnus Nørgård; Nils Axel Andersen; Niels Kjølstad Poulsen; Ole Ravn

doi:10.1109/AMC.1998.743533

Location Estimation using Delayed Measurements

Martin Bak, Thomas Dall Larsen, Peter Magnus Nørgård, Nils Axel Andersen, Niels Kjølstad Poulsen, Ole Ravn

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

When combining data from various sensors it is vital to acknowledge possible measurement delays. Furthermore, the sensor fusion algorithm, often a Kalman filter, should be modified in order to handle the delay. The paper examines different possibilities for handling delays and applies a new technique to a sensor fusion system for estimating the location of an autonomous guided vehicle. The system fuses encoder and vision measurements in an extended Kalman filter. Results from experiments in a real environment are reported

Original language	English
Title of host publication	Advanced Motion Control, 1998. AMC '98-Coimbra., 1998 5th International Workshop on
Publisher	IEEE
Publication date	1998
Pages	180-185
ISBN (Print)	0-7803-4484-7
DOIs	https://doi.org/10.1109/AMC.1998.743533
Publication status	Published - 1998
Event	International Workshop on Advanced Motion Control, AMC '98 - Coimbra, Portugal Duration: 1 Jan 1998 → …

Conference

Conference	International Workshop on Advanced Motion Control, AMC '98
City	Coimbra, Portugal
Period	01/01/1998 → …

Bibliographical note

Copyright: 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

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title = "Location Estimation using Delayed Measurements",

abstract = "When combining data from various sensors it is vital to acknowledge possible measurement delays. Furthermore, the sensor fusion algorithm, often a Kalman filter, should be modified in order to handle the delay. The paper examines different possibilities for handling delays and applies a new technique to a sensor fusion system for estimating the location of an autonomous guided vehicle. The system fuses encoder and vision measurements in an extended Kalman filter. Results from experiments in a real environment are reported",

author = "Martin Bak and Larsen, {Thomas Dall} and N{\o}rg{\aa}rd, {Peter Magnus} and Andersen, {Nils Axel} and Poulsen, {Niels Kj{\o}lstad} and Ole Ravn",

note = "Copyright: 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE; International Workshop on Advanced Motion Control, AMC '98 ; Conference date: 01-01-1998",

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AU - Larsen, Thomas Dall

AU - Nørgård, Peter Magnus

AU - Andersen, Nils Axel

AU - Poulsen, Niels Kjølstad

AU - Ravn, Ole

N1 - Copyright: 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

PY - 1998

Y1 - 1998

N2 - When combining data from various sensors it is vital to acknowledge possible measurement delays. Furthermore, the sensor fusion algorithm, often a Kalman filter, should be modified in order to handle the delay. The paper examines different possibilities for handling delays and applies a new technique to a sensor fusion system for estimating the location of an autonomous guided vehicle. The system fuses encoder and vision measurements in an extended Kalman filter. Results from experiments in a real environment are reported

AB - When combining data from various sensors it is vital to acknowledge possible measurement delays. Furthermore, the sensor fusion algorithm, often a Kalman filter, should be modified in order to handle the delay. The paper examines different possibilities for handling delays and applies a new technique to a sensor fusion system for estimating the location of an autonomous guided vehicle. The system fuses encoder and vision measurements in an extended Kalman filter. Results from experiments in a real environment are reported

U2 - 10.1109/AMC.1998.743533

DO - 10.1109/AMC.1998.743533

M3 - Article in proceedings

SN - 0-7803-4484-7

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EP - 185

BT - Advanced Motion Control, 1998. AMC '98-Coimbra., 1998 5th International Workshop on

PB - IEEE

T2 - International Workshop on Advanced Motion Control, AMC '98

Y2 - 1 January 1998

ER -

Location Estimation using Delayed Measurements

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