Handles the data acquisition and processing from IMU sensors, providing orientation and motion data to enhance the tracking capabilities of the system.

Realtime data viewer and processor (in Python)

Dockerized ROS2 stack for the WATonomous Autonomous Driving Software Pipeline

A powerful firmware for Aerosentinel Icarus Flight Module.

The Laserscan and Pointcloud Combiner is a ROS 1 node that can combine PointCloud2 and LaserScan input sources by selecting the nearest detection. The computed nearest detection is converted to the laserscan format and published to a LaserScan topic. The package supports at most 1 PointCloud2 source and 2 LaserScan sources.

Official implementation of αLiDAR: An Adaptive High-Resolution Panoramic LiDAR System

ROS/ROS2 -- Navigation, Manipulation, Mimicking, Sensor Fusion, VR, Speech Recogition, Activity Recognition, Computer Vision

Software for guidance, navigation and control for the Vortex AUVs. Purpose built for competing in AUV/ROV competitions.

Stream real-time Android sensor data over UDP with low-latency

A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry (LIVO).

Roll control system for the IREC 2020-21 rocket (Endurance) and Drag control system for the IREC 2021-22 rocket (Intrepid)

Bumperbot is an open-source 3D printed self-driving robot powered by ROS 2. Its simple design and low cost make it an excellent learning platform, featured in the "Self Driving and ROS 2 - Learn by Doing! Odometry & Control" and "Self Driving and ROS 2 - Learn by Doing! Map & Localization" courses.

This project aims to explore and compare different Kalman filter architectures and their performance on FPGA platforms. The focus is on two main applications: IMU sensor fusion for quadcopters and prediction in power electronics for microgrid renewable energy systems.

Autonomous Mobile Robot developed and programmed in the online course named "Self-Driving and ROS 2 - Learn By Doing! Odometry & Control"

Course of Sensor Fusion Nanodegree program on Udacity.

PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)

This is a 3D multi-object tracking algorithm using 2D bounding box detection from multiple cameras viewing the scene at different angles. The core algorithm is implemented in C++ with Python wrapper.

Line follower, platooning, sensor fusion with DroidControlSystem and etc.

A method used sliding window filter frame work for RTK-Visual-Inertial-Navigation

Autonomous Mobile Robot developed and programmed in the online course named "Self-Driving and ROS - Learn By Doing! Odometry & Control"