Feasibility study of partial observability in H filtering for robot localization and mapping problem

Hamzah Ahmad, Toru Namerikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

This paper presents H Filter SLAM, which is also known as the minimax filter to estimate the robot and landmarks location with the analysis on partial observability. Some convergence conditions are also presented to aid the analysis. Due to SLAM is a controllable but unobservable problem, it's difficult to estimate the position of robot and landmarks even though the control inputs are given to the system. As a result, Covariance Inflation which is a method of adding a pseudo positive semidefinite(PsD) matrix is proposed as one approach to analyze Partial Observability effects in SLAM and to reduce the computation cost. H Filter is capable of withstand non-gaussian noise characteristics and therefore, may provide another available approach towards SLAM solution.

Original languageEnglish
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
Pages3980-3985
Number of pages6
Publication statusPublished - 2010 Oct 15
Event2010 American Control Conference, ACC 2010 - Baltimore, MD, United States
Duration: 2010 Jun 302010 Jul 2

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

Other

Other2010 American Control Conference, ACC 2010
CountryUnited States
CityBaltimore, MD
Period10/6/3010/7/2

ASJC Scopus subject areas

  • Control and Systems Engineering

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    Ahmad, H., & Namerikawa, T. (2010). Feasibility study of partial observability in H filtering for robot localization and mapping problem. In Proceedings of the 2010 American Control Conference, ACC 2010 (pp. 3980-3985). [5531214] (Proceedings of the 2010 American Control Conference, ACC 2010).