Sensor Fusion
Showing 29 of 65 projects
A ROS2 package for calibrating robot parameters like camera intrinsics, joint offsets, and frame transforms via optimization.
A Python implementation for fully automatic extrinsic calibration of 3D LiDAR and cameras using laser reflectance intensity.
A neural network for object detection using multi-level fusion of camera and radar data, built on Keras RetinaNet.
A ROS library for LiDAR point cloud segmentation, enabling ground removal and object clustering for autonomous vehicle perception.
A real-time ROS 2 package for detecting drivable roads and sidewalks from LIDAR point clouds in urban autonomous driving scenarios.
A C++ library implementing the Responsibility Sensitive Safety (RSS) model for autonomous vehicle decision-making.
A MicroPython library implementing the Madgwick algorithm for sensor fusion, calculating heading, pitch, and roll from motion tracking devices.
A full LiDAR SLAM system for static environment mapping using LiDAR with optional GPS, IMU, and odometry support.
A robust C++ sensor fusion library for online localization using factor graphs and least squares optimization.
A ROS driver for TI mmWave radar sensors with sensor fusion, multi-radar support, and camera overlay capabilities.
A ROS-based dataset and tools for autonomous vehicle development with seasonal multi-sensor data from Ford vehicles.
A curated list of top-tier publications and resources for LiDAR-Visual fusion SLAM systems.
A ROS stack providing perception packages for 2D image and 3D point cloud processing in robotics.
A real-time fiducial tag system for LiDAR point clouds, robust to lighting and compatible with visual markers like AprilTags.
A Python devkit for loading, exploring, and manipulating the PandaSet, a large-scale autonomous driving dataset with LiDAR, camera, and annotations.
MicroPython drivers for InvenSense MPU9250, MPU9150, and MPU6050 IMUs, providing calibrated sensor data for motion tracking.
Converts KITTI autonomous driving dataset raw data to ROS bags and provides a C++ library for direct data access.
ROS package for sensor processing, object detection, tracking, and evaluation using the KITTI Vision Benchmark dataset.
A recursive B-spline-based state estimation framework for 6-DoF LiDAR odometry, supporting LiDAR-only, LiDAR-inertial, and multi-LiDAR configurations.
A large-scale driving behavior dataset with LiDAR point clouds, dashboard videos, and sensor data for autonomous driving research.
A tool for calibrating event cameras by converting event data to images and using standard image-based calibration toolboxes.
A MicroPython I2C driver for the MPU9250 9-axis motion tracking sensor, providing accelerometer, gyroscope, and magnetometer data.
A ROS catkin package for correcting motion distortion in LiDAR scans using external 6DoF pose estimation.
A robust, low-drift, real-time SLAM package for the Livox Horizon LiDAR, designed for highway autonomous driving scenarios.
A Go library implementing state estimation and filtering algorithms including Kalman, Extended Kalman, Unscented Kalman, and Particle filters.
A JavaScript implementation of the Kalman filter for state estimation in noisy systems.
A ROS filter that removes points belonging to a robot's own body from laser scans and point clouds.
A ROS 2 node for real-time LiDAR ground segmentation using a two-phase grid-based algorithm for robotic perception.
A MicroPython driver for the Bosch BNO055 IMU, providing hardware sensor fusion for orientation, acceleration, and magnetic field data.
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