Evaluation of the applicability of state estimation filters for indoor robot positioning
Abstract
The results show that the EKF has advantages in processing speed and low computational cost, making it suitable for real-time systems, though it remains sensitive to noise and highly nonlinear models. The UKF demonstrates a balance between estimation accuracy and computational efficiency due to its ability to provide reliable estimates under nonlinear conditions without increasing computational cost. The PF offers high stability and the ability to handle non-Gaussian noise; however, it requires significant computational resources, especially when the number of particles is large.
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DOI: http://dx.doi.org/10.21553/rev-jec.445
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