📈 Human Motion Tracking with Kalman Filter Estimate the true velocity (and later, orientation) of a smartphone using accelerometer and gyroscope data from the UCI HAR Dataset. This project applies a ...

Kalman and Bayesian Filters in Python Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Jupyter Notebook so that you can run and ...

Keywords: object position tracking, object velocity tracking, differentiable extended kalman filtering, machine learning-aided filtering, humanoid robotics Citation: Piga NA, Pattacini U and Natale L ...

This paper proposes a 6D object pose tracking algorithm, called MaskUKF, that combines deep object segmentation networks and depth information with a serial Unscented Kalman Filter to track the pose ...

Developing an indoor location tracking system based on the Received Signal Strength Indicator (RSSI) of the Wireless Local Area Network (WLAN) is considered cost effective method. The widely used ...

Tracking multiple targets in dynamic settings poses significant challenges in fields like robotics and surveillance. This process requires detecting and estimating object trajectories while addressing ...

Applies this understanding to enhancing the robustness of the filter and to extend to applications including prediction and smoothing. Shows how to implement a target-tracking application in Octave ...

Therefore, the filter like the Maximum Correntropy Kalman Filter (MCKF) could not achieve the good performance under some complex non-Gaussian noise.