FAST-Calib is a ROS-based application for LiDAR-camera extrinsic calibration that uses a target-based approach with ArUco markers and circular holes. The system processes synchronized camera images and LiDAR point clouds to detect calibration target features in both modalities, then computes the extrinsic transformation between sensor frames. It supports both solid-state (Livox) and mechanical (Ouster, Hesai) LiDAR sensors through adaptive preprocessing pipelines. The application includes single-scene calibration for immediate results and multi-scene joint calibration for improved accuracy. Key components include modular LiDAR and camera processing pipelines, geometric validation for target detection, and coordinate transformation utilities.
This repository implements FAR Planner (Fast, Attemptable Route Planner using Dynamic Visibility Update), a robotic navigation system designed for subterranean environments. It builds and dynamically updates a visibility graph from LiDAR point cloud data to enable fast replanning in static and dynamic environments. The system uses a modular ROS architecture with separate components for contour detection, graph management, path planning, terrain handling, and sensor processing. Key features include dual-threaded operation (graph update and path search), RViz visualization, teleoperation capabilities, and integration with custom ROS message types for graph communication. The code was field-tested by the CMU-OSU Team in the DARPA Subterranean Challenge, where it won the 'Most Sectors Explored Award'.