Adaptive Observation Covariance for EKF-SLAM in Indoor Environments using Laser Data

Vázquez-Martín, Ricardo; Núñez, Pedro; Toro, J.C. del; Bandera, Antonio; Sandoval, F.

doi:10.1109/melcon.2006.1653134

Cited by 5 publications

(4 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…6, the adaptive curvature function can directly provide three different natural landmarks: line segments, corners and curve segments [24]. However, in order to include these items as landmarks in an EKF-based SLAM algorithm [33], it is necessary to characterise them by a set of invariant parameters and moreover, to estimate their uncertainties. This is typically achieved by fitting parametric curves to measurement data associated with each line or curve segment and evaluating the uncertainty associated with the measured data.…”

Section: Natural Landmark Extraction and Characterisationmentioning

confidence: 99%

Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation

Núñez

Vázquez-Martín

Toro

et al. 2008

Robotics and Autonomous Systems

Self Cite

View full text Add to dashboard Cite

Section: Natural Landmark Extraction and Characterisationmentioning

confidence: 99%

Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation

Núñez

Vázquez-Martín

Toro

et al. 2008

Robotics and Autonomous Systems

Self Cite

View full text Add to dashboard Cite

“…Among the SLAM algorithms, EKF-based SLAM shows its competency to solve the problem. Due to the simplicity of the algorithm, EKF SLAM has been widely used in many applications [ 5 , 6 ]. However, the shortcomings of EKF SLAM are also exposed at the same time.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

Liu

Dong

Shen

et al. 2015

Sensors

View full text Add to dashboard Cite

In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles. The proposed algorithm solves the measurement update equations with iterative methods adaptively to reduce linearization errors. With the scalability advantage being kept, the consistency and accuracy of SEIF is improved. Simulations and practical experiments were carried out with both a land car benchmark and an autonomous underwater vehicle. Comparisons between iterative SEIF (ISEIF), standard EKF and SEIF are presented. All of the results convincingly show that ISEIF yields more consistent and accurate estimates compared to SEIF and preserves the scalability advantage over EKF, as well.

show abstract

“…Recently, various SLAM arithmetic are put forward under different background such as indoor [4], outdoor [5], underwater [6] and aerospace [7] and so on. The main SLAM methods include EKF(Extended Kalman Filter), UKF(Unscented Kalman Filter) and PF(Particle Filter) .…”

Section: Introductionmentioning

confidence: 99%

Study on Application of STF in Mobile Robot SLAM

Zeng¹,

Jing²,

Song³

et al. 2009

2009 International Conference on Information Engineering and Computer Science

View full text Add to dashboard Cite

According to the operation characteristics of mobile robots, the common SLAM methods of robot are analyzed and the it is proposed that STF can be applied in SLAM of mobile robots. Combining the advantages of STF arithmetic, the problems in surroundings mapping and robot localization such as unknown robot model and discontinuity of state change and so on are solved by introducing gradually eliminating factor. Experimental results show that the localization with this method is more precise than that with other methods, and thus can satisfy the requirement of SLAM in large scale indoor environment.

show abstract

Adaptive Observation Covariance for EKF-SLAM in Indoor Environments using Laser Data

Cited by 5 publications

References 11 publications

Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation

Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

Study on Application of STF in Mobile Robot SLAM

Contact Info

Product

Resources

About