Improving the performance of the EKF-SLAM algorithm in dynamic environments using ANFIS
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
The issue of Simultaneous localization and mapping (SLAM) in dynamic environments is an important object in the navigation of autonomous robots, which has not yet been investigated much. In this paper, by presenting a new method, we track dynamic objects in the environment simultaneously with living static object. For this purpose, the EKFSLAM algorithm has been developed for dynamic environments in the way that simultaneous mapping and mapping of dynamic objects in the environment are solved in the form of a problem, which was previously done individually. Also, considering that the efficiency and performance of the developed Kalman filter algorithm depend heavily on the correct knowledge of the covariance matrix of observations, an adaptive Neuro-Fuzzy inference system (ANFIS) is used to adjust the measurement noise covariance matrices to ensure that the accuracy and consistency of the algorithm Than other older methods (SLAM and DATMO, FastSLAM, EKF) is guaranteed. The results of the experiments indicate that the proposed algorithm performs precise tracking
Keywords:
Language:
Persian
Published:
Journal of Mechanical Engineering, Volume:52 Issue: 2, 2022
Pages:
51 to 58
https://magiran.com/p2443142
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