Autonomous Mobile Robot developed and programmed in the online course named "Self-Driving and ROS - Learn By Doing! Odometry & Control"
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Updated
Jun 20, 2024 - C++
Autonomous Mobile Robot developed and programmed in the online course named "Self-Driving and ROS - Learn By Doing! Odometry & Control"
A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry (LIVO).
SurfaceGPS: Multi-modal Localization for Facade Robots
Realtime data viewer and processor (in Python)
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.
Notes I took/used for passing Sensor Fusion Nanodegree
Ground-Fusion: A Low-cost Ground SLAM System Robust to Corner Cases (ICRA2024)
FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry
A method used sliding window filter frame work for RTK-Visual-Inertial-Navigation
ROS/ROS2 -- Navigation, Manipulation, Mimicking, Sensor Fusion, VR, Speech Recogition, Activity Recognition, Computer Vision
Autonomous Mobile Robot developed and programmed in the online course named "Self-Driving and ROS 2 - Learn By Doing! Odometry & Control"
StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation
Software for guidance, navigation and control for the Vortex AUVs. Purpose built for competing in AUV/ROV competitions.
M-MOVE-IT is multi-type data labeling and annotation tool with standardized output format. This till simplifies the proces for multimodal annotation and synchronizes sensors. This repo is forked from labelstudio.
Dockerized ROS2 stack for the the WATonomous Autonomous Driving Software Pipeline
A free Dynamic Network (DN) solver that runs online in the browser. ODyN fuses information from cameras, GNSS and inertial sensors in a single adjustment and it can be used to estimate a high-frequency trajectory for precise direct geo-referencing, to improve photogrammetric reconstructions in challenging scenarios or to determine several types …
A curated list of efficient deep learning.
IMU + X(GNSS, 6DoF Odom) Loosely-Coupled Fusion Localization based on ESKF, IEKF, UKF(UKF/SPKF, JUKF, SVD-UKF) and MAP
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