Stars
A multi-stack, ETSI compliant, V2X framework for ns-3.
Network Simulation for Urban Mobility: Interface between ns-3 and SUMO. The project allow user to control ns-3 LTE module and the UE mobility from SUMO. (developed by Wireless and Mobile Networking…
Blender add-on for creating OpenDRIVE and OpenSCENARIO based automotive driving scenarios including 3D models
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
A Package for Camera, IMU, Lidar Joint Calibration.
[ECCV2022] Official Implementation of paper "V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer"
A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
Coursera Open Courses from University of Toronto
Repository for GNSS-based position estimation using a Deep Neural Network
AutoMerge: A Framework for Map Assembling and Smoothing in City-scale Environments
Implementation for the paper: AutoPlace: Robust Place Recognition with Single-chip Automotive Radar
Convert images of LaTex math equations into LaTex code.
Integration of AutoWare AV software with the CARLA simulator
Collaborative sensing in heterogeneous multi-robot systems with collaborative UWB-based localization.
This extended Kalman filter combines IMU, GNSS, and LIDAR measurements to localize a vehicle using data from the CARLA simulator.
Robust Odometry and Mapping for Multi-LiDAR Systems with Online Extrinsic Calibration
DamonMIN / imu_utils
Forked from gaowenliang/imu_utilsA ROS package tool to analyze the IMU performance.
Some tools for the recent papers on driver assistance strategies
A ROS package tool to analyze the IMU performance.
The official pylon ROS driver for Basler GigE Vision and USB3 Vision cameras:
This is the implementation of YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design
Model to predict the multipath anomaly in GPS L1 C/A signals
MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).