Invariant EKF based 2D Active SLAM with Exploration Task

Xu，Mengya1,2; Song，Yang1; Chen，Yongbo1; Huang，Shoudong1; Hao，Qi2

10.1109/ICRA48506.2021.9561951

2021

IEEE International Conference on Robotics and Automation (ICRA)

1050-4729

2577-087X

978-1-7281-9078-5

Proceedings - IEEE International Conference on Robotics and Automation

2021-May

5350-5356

MAY 30-JUN 05, 2021

null,Xian,PEOPLES R CHINA

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Right invariant extended Kalman filter (RIEKF) based simultaneous localization and mapping (SLAM) proposed recently has shown to be able to produce more consistent SLAM estimates as compared with traditional EKF based SLAM methods, including some improved EKF SLAM methods such as observability constrained-EKF (OC-EKF) SLAM. Latest results have demonstrated that its performance is very close to optimization based SLAM algorithms such as iSAM. In this paper, we propose to use RIEKF SLAM algorithm in active SLAM where both the predicted SLAM results for choosing control actions and the actual estimated SLAM results applying the selected control actions are computed using RIEKF algorithms. The advantages over traditional EKF based active SLAM are the more accurate and consistent predicted uncertainty estimates which result in robustness of the active SLAM algorithm. The advantages over optimization based active SLAM is the reduced computational cost. Simulation results are presented to validate the advantages of the proposed algorithm

Simultaneous localization and mapping Uncertainty Simulation Conferences Prediction algorithms Robustness Kalman filters

其他

英语

CPCI-S ; EI

Automation & Control Systems ; Robotics

Automation & Control Systems ; Robotics

WOS:000765738804019

20220911738241

Robotics ; Uncertainty analysis

Robotics:731.5 ; Probability Theory:922.1

2-s2.0-85125452499

Scopus

1.Centre for Autonomous Systems,University of Technology,Sydney,2008,Australia
2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China

Xu，Mengya,Song，Yang,Chen，Yongbo,et al. Invariant EKF based 2D Active SLAM with Exploration Task[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:5350-5356.