Computer Engineering

Previous Articles    

SLAM Algorithm of Iterated Square Root Cubature Kalman Filtering

TAO Ming,LING Youzhu,CHEN Mengyuan,DAI Xuemei   

  1. (Anhui Key Laboratory of Electric Drive and Control,Anhui Polytechnic University,Wuhu 241000,China)
  • Received:2014-12-05 Online:2015-09-15 Published:2015-09-15

Abstract: The disadvantage of Square Root Cubature Kalman Filtering(SR-CKF)algorithm on the Simultaneous Location and Mapping(SLAM)is that with map feature points increasing,the volume points deviate from the ideal trajectory to cause great defects in state estimation.In order to solve that problem,this paper provides an improved square root cubature Kalman filtering algorithm.The algorithm takes advantage of iterative method of the measurement update,which makes the sampling points less distortion and further improves the accuracy in the highly nonlinear environment.Simulation results show that,compared with SR-CKF algorithm,this algorithm can effectively improve the accuracy of position and attitude.

Key words: iteration, Simultaneous Localization and Mapping(SLAM), sampling, Extended Kalman Filtering(EKF), weighted processing

CLC Number: