Perception
Showing 29 of 29 projects
An open-source, high-performance platform for developing, testing, and deploying autonomous vehicles.
A co-simulation framework for prototyping and evaluating cooperative driving automation applications using CARLA and SUMO.
A ROS package collection for processing raw camera images into calibrated, rectified formats for computer vision applications.
ROS packages for interfacing with Velodyne 3D LIDAR sensors in robotics applications.
Bridge between ROS 2 and OpenCV for real-time computer vision applications.
Bridge between ROS 2 and OpenCV for real-time computer vision applications.
A ROS/ROS2 bridge enabling two-way communication between the CARLA autonomous driving simulator and ROS ecosystems.
An OpenAI Gym environment wrapper for the CARLA autonomous driving simulator, enabling reinforcement learning research.
ROS 2 package for bidirectional conversion between 3D point clouds and 2D laser scans.
A fast and robust ground segmentation algorithm for 3D LiDAR point clouds, using concentric zone-based region-wise processing.
A benchmark dataset for long-range (up to 250m) dense depth estimation in autonomous driving, featuring 360° LiDAR ground truth.
A modular autonomous driving platform for developing and testing AV components on CARLA simulator and real-world vehicles.
A simple, robust, and accurate 3D LiDAR SLAM system designed to just work.
A ROS driver for Livox LiDAR devices (Mid-40, Mid-70, Tele-15, Horizon, Avia) to publish point cloud data.
ROS & ROS2 implementation of Patchwork++, a fast and robust ground segmentation method for 3D LiDAR point clouds.
A real-time ROS 2 package for detecting drivable roads and sidewalks from LIDAR point clouds in urban autonomous driving scenarios.
A ROS-based dataset and tools for autonomous vehicle development with seasonal multi-sensor data from Ford vehicles.
A ROS stack providing perception packages for 2D image and 3D point cloud processing in robotics.
A C++ library with Python bindings for robotic motion planning and decision making, integrated with DART and OMPL.
A ROS library for robust plane segmentation from LIDAR, depth camera data, and elevation maps using normal-based clustering.
A deep learning model for joint perception and motion prediction in autonomous driving using bird's eye view maps.
A ROS catkin package for correcting motion distortion in LiDAR scans using external 6DoF pose estimation.
ROS2 package for 3D occupancy grid mapping using OctoMap, enabling real-time environment modeling.
A ROS2 wrapper for real-time object detection, 3D localization, and tracking using RGB-D camera inputs.
A ROS 2 node for real-time LiDAR ground segmentation using a two-phase grid-based algorithm for robotic perception.
A high-precision, grid-based C++ library for ground segmentation in LiDAR point clouds, designed for safety-critical autonomous driving and robotics.
A curated collection of machine-learned models for autonomous driving tasks like perception, prediction, and planning.
ROS2 driver for Denso Toyota/Lexus 2015-2017 radar units, enabling autonomous vehicle perception.
A ROS package for connecting the Waymo Open Dataset to the Robot Operating System (ROS).
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