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This package introduces the concept of optimizing target shape to remove pose ambiguity for LiDAR point clouds. Both the simulation and the experimental results confirm that by using the optimal shape and the global solver, we achieve centimeter error in translation and a few degrees in rotation even when a partially illuminated target is placed…
A research-purposed, GUI-powered, Python-based framework that allows easy development of dynamic point-cloud (and accompanying image) data processing pipelines.
This package introduces the concept of optimizing target shape to remove pose ambiguity for LiDAR point clouds. Both the simulation and the experimental results confirm that by using the optimal shape and the global solver, we achieve centimeter error in translation and a few degrees in rotation even when a partially illuminated target is placed…
ADAS Car - with Collision Avoidance System (CAS) - on Indian Roads using LIDAR-Camera Low-Level Sensor Fusion. DIY Gadget built with Raspberry Pi, RP LIDAR A1, Pi Cam V2, LED SHIM, NCS 2 and accessories like speaker, power bank etc
MultiCorrupt: A benchmark for robust multi-modal 3D object detection, evaluating LiDAR-Camera fusion models in autonomous driving. Includes diverse corruption types (e.g., misalignment, miscalibration, weather) and severity levels. Assess model performance under challenging conditions.
This repository uses a ROS node to subscribe to camera (hikvision) and lidar (livox) data. After the node merges the data, it publishes the colored point cloud and displays it in rviz.
[T-RO 2022] Official Implementation for "LiCaS3: A Simple LiDAR–Camera Self-Supervised Synchronization Method," in IEEE Transactions on Robotics, doi: 10.1109/TRO.2022.3167455.