Experiments in sensor fusion

Synthesize, analyze, and visualize biological oceanography data

Code and material related to PhD thesis: The Dark Side of Decentralized Target Tracking

A user-friendly toolkit for engineers and researchers to address the problem of aligning measurements from gyroscopes mounted on the same rigid body.

Executed sensor fusion by implementing a Complementary Filter to get an enhanced estimation of the vehicle’s overall trajectory, especially in GPS-deprived environments.

Sensor fusion in vehicle localisation and tracking is a powerful technique that combines multiple data sources for enhanced accuracy. This project applies and compares two TDOA sensor networks and WLS and Kalman Filter based localisation and tracking techniques.

This repository contains different algorithms for attitude estimation (roll, pitch and yaw angles) from IMU sensors data: accelerometer, magnetometer and gyrometer measurements

The Differential Robot project is a fully autonomous robot designed to navigate around a track, avoid obstacles, and simultaneously map the surroundings. This project was developed as a course project for Autonomous Robotics at Dalhousie University.

Tools to process data from the INSANE data set

A MATLAB and Simulink project. Includes controller design, Simscape simulation, and sensor fusion for state estimation. By: Matteo Liguori; Supervisor and Collaborator: Francesco Ciriello Professor at King's College London

Quaternion-based Kalman filter for attitude estimation from IMU data

Data Fusion via Quaternions for MPU-6050 Accelerometer & Gyroscope

Kalman filter implementation and design

Time-Varying Kalman Attitude Estimator. An algorithm for attitude estimation from magnetic, angular rate, and gravity sensors data.

Linear, Extended & Unscented Kalman filter Fusion Models for 2D tracking

Semester project for my Robotic Sensing and Navigation course: Fusing pedestrian detection outputs from RGB, IR, and LiDAR sensors.

Computed Visual Odometry using corner extraction from April Tags and optical flow using ORB

This is a repository of the Open Aided Navigation project. The project aims to demonstrate and explain state of the art methods of modern aided inertial and satellite (GNSS) navigation, and multi-sensor localization. The software provided in this repository is written in Matlab.

This model include; plant,controller,sensor,filter and disturbance models.

In this repository, Multidimensional Kalman Filter and sensor fusion are implemented to predict the trajectories for constant velocity model. Data is extracted from GPS and Accelerometer using mobile phone. It is apart of Assignment3 in Sensing, Perception and Actuation course for ROCV master's program at Innopolis University.