Information-based reduced landmark SLAM

Siddharth Choudhary; Vadim Indelman; Henrik I. Christensen; Frank Dellaert

doi:10.1109/ICRA.2015.7139839

Information-based reduced landmark SLAM

Siddharth Choudhary, Vadim Indelman, Henrik I. Christensen, Frank Dellaert

Aerospace Engineering

Technion - Israel Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

Abstract

In this paper, we present an information-based approach to select a reduced number of landmarks and poses for a robot to localize itself and simultaneously build an accurate map. We develop an information theoretic algorithm to efficiently reduce the number of landmarks and poses in a SLAM estimate without compromising the accuracy of the estimated trajectory. We also propose an incremental version of the reduction algorithm which can be used in SLAM framework resulting in information based reduced landmark SLAM. The results of reduced landmark based SLAM algorithm are shown on Victoria park dataset and a Synthetic dataset and are compared with standard graph SLAM (SAM [6]) algorithm. We demonstrate a reduction of 40-50% in the number of landmarks and around 55% in the number of poses with minimal estimation error as compared to standard SLAM algorithm.

Original language	English
Article number	7139839
Pages (from-to)	4620-4627
Number of pages	8
Journal	Proceedings - IEEE International Conference on Robotics and Automation
Volume	2015-June
Issue number	June
DOIs	https://doi.org/10.1109/ICRA.2015.7139839
State	Published - 29 Jun 2015
Event	2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States Duration: 26 May 2015 → 30 May 2015

All Science Journal Classification (ASJC) codes

Software
Control and Systems Engineering
Artificial Intelligence
Electrical and Electronic Engineering

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10.1109/ICRA.2015.7139839

Cite this

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title = "Information-based reduced landmark SLAM",

abstract = "In this paper, we present an information-based approach to select a reduced number of landmarks and poses for a robot to localize itself and simultaneously build an accurate map. We develop an information theoretic algorithm to efficiently reduce the number of landmarks and poses in a SLAM estimate without compromising the accuracy of the estimated trajectory. We also propose an incremental version of the reduction algorithm which can be used in SLAM framework resulting in information based reduced landmark SLAM. The results of reduced landmark based SLAM algorithm are shown on Victoria park dataset and a Synthetic dataset and are compared with standard graph SLAM (SAM [6]) algorithm. We demonstrate a reduction of 40-50\% in the number of landmarks and around 55\% in the number of poses with minimal estimation error as compared to standard SLAM algorithm.",

author = "Siddharth Choudhary and Vadim Indelman and Christensen, \{Henrik I.\} and Frank Dellaert",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 IEEE International Conference on Robotics and Automation, ICRA 2015 ; Conference date: 26-05-2015 Through 30-05-2015",

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doi = "10.1109/ICRA.2015.7139839",

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T1 - Information-based reduced landmark SLAM

AU - Choudhary, Siddharth

AU - Indelman, Vadim

AU - Christensen, Henrik I.

AU - Dellaert, Frank

PY - 2015/6/29

Y1 - 2015/6/29

N2 - In this paper, we present an information-based approach to select a reduced number of landmarks and poses for a robot to localize itself and simultaneously build an accurate map. We develop an information theoretic algorithm to efficiently reduce the number of landmarks and poses in a SLAM estimate without compromising the accuracy of the estimated trajectory. We also propose an incremental version of the reduction algorithm which can be used in SLAM framework resulting in information based reduced landmark SLAM. The results of reduced landmark based SLAM algorithm are shown on Victoria park dataset and a Synthetic dataset and are compared with standard graph SLAM (SAM [6]) algorithm. We demonstrate a reduction of 40-50% in the number of landmarks and around 55% in the number of poses with minimal estimation error as compared to standard SLAM algorithm.

AB - In this paper, we present an information-based approach to select a reduced number of landmarks and poses for a robot to localize itself and simultaneously build an accurate map. We develop an information theoretic algorithm to efficiently reduce the number of landmarks and poses in a SLAM estimate without compromising the accuracy of the estimated trajectory. We also propose an incremental version of the reduction algorithm which can be used in SLAM framework resulting in information based reduced landmark SLAM. The results of reduced landmark based SLAM algorithm are shown on Victoria park dataset and a Synthetic dataset and are compared with standard graph SLAM (SAM [6]) algorithm. We demonstrate a reduction of 40-50% in the number of landmarks and around 55% in the number of poses with minimal estimation error as compared to standard SLAM algorithm.

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DO - 10.1109/ICRA.2015.7139839

M3 - مقالة من مؤنمر

SN - 1050-4729

VL - 2015-June

SP - 4620

EP - 4627

JO - Proceedings - IEEE International Conference on Robotics and Automation

JF - Proceedings - IEEE International Conference on Robotics and Automation

IS - June

M1 - 7139839

T2 - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015

Y2 - 26 May 2015 through 30 May 2015

ER -

Information-based reduced landmark SLAM

Abstract

All Science Journal Classification (ASJC) codes

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