Stars
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping
Control and Trajectory Tracking for Autonomous Vehicles
Sensor-Fusion-and-Object-Tracking-2
Object (e.g Pedestrian, biker, vehicles) tracking by Kalman Filter (KF), with fused data from both lidar and radar sensors.
The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++
A ROS node providing a driver interface to the Roboclaw motor controller.
Move Base Flex: a backwards-compatible replacement for move_base
ROS packages for Turtlebot3
basavarajnavalgund / husky
Forked from husky/huskyCommon packages for the Clearpath Husky
Udacity Robotics Home Service Robot Project
Personalization of Assistive Driving in Carla Simulator
This project is to use Model Predictive Control (MPC) to drive a car in a game simulator. The server provides reference waypoints (yellow line in the demo video) via websocket, and we use MPC to co…
Sensor fusion-based localization using robot-localization package
Autonomous Mobile Robot (AMR), a holonomic drive with 4 mecanum-wheels. It autonomously maps an environment, localizes itself, and navigate to pick-up and drop-off objects in a simulated environment.
Implemented a C++ particle filter for real-time vehicle localization with only current visual observations and a map.
Implemented a simple real-time path planner in C++ to navigate a car around a simulated highway scenario
Object (e.g Pedestrian, biker, vehicles) tracking by Unscented Kalman Filter (UKF), with fused data from both lidar and radar sensors.