Particle filters while not abandoned have become quite rare. Nowadays they are really only used to solve localization problems. The reason being that they are quite expensive (each particle essentially stores the entire state) so 50 particles would be 50 times as expensive as an EKF. Also its other two benefits
- Being able to handle non gaussian noise distributions
- Handling multi modal distributions
Just don't end up being so important in practice. At least not worth the additional computation cost.
EKF's ,however, nowadays are still used a bunch. Typically they are paired together with a pose graph optimization algorithm. Where the EKF part estimates the current pose(and usually some sort of sliding window of past poses), and those then get fed into backend of all past poses(this is almost always solved with factor graph/optimization based approaches).
An example of this is approach is OpenVINS when paired with ov_secondary.
You still have some papers that solve the whole SLAM problem local and global in one EKF framework such as https://arxiv.org/pdf/1903.08636.pdf.