Projects sharing features with Cartographer

FAST_LIO is a real-time SLAM system and LiDAR-inertial odometry package designed for simultaneous localization and mapping. It functions as a state estimation engine and 3D mapping tool that fuses LiDAR point clouds with inertial measurement unit data to provide robust robot state estimation. The system utilizes a tightly-coupled sensor fusion approach with an iterative Kalman filter to estimate position and orientation. It distinguishes itself through direct point-to-plane matching, which calculates odometry by matching raw lidar points to the map surface without manual geometric feature ext

This project is a robotics software package designed for simultaneous localization and mapping, providing a framework for visual-inertial odometry and environmental mapping. It functions as a middleware-integrated library that enables autonomous mobile robots to estimate their position and orientation by processing sensor data within modular software systems. The library distinguishes itself by utilizing hardware-accelerated processing to perform feature tracking and odometry calculations on dedicated graphics hardware. It maintains spatial accuracy through graph-based optimization and statis

The Android ARCore SDK is a software development kit and augmented reality framework used to create experiences on Android devices. It provides a collection of tools and native libraries for tracking device motion and mapping physical environments to place virtual objects in real space. The framework utilizes an environmental tracking API to detect physical planes and estimate ambient lighting, which blends digital content with the real world. It includes systems for fixing virtual content to specific physical locations to maintain spatial stability as a user moves through an environment. Th

OM1 is a multimodal AI agent runtime and orchestration framework designed to connect large language models to physical robot hardware and sensors. It provides an execution environment that processes audio, video, and sensor data to drive autonomous decisions and actions in real-world settings. The system integrates a robotics SLAM and navigation stack with a hardware abstraction layer, allowing high-level AI commands to be translated into low-level motor and actuator instructions. It distinguishes itself by incorporating blockchain-based governance to enforce immutable operational rules and p

pyslam is a framework for Simultaneous Localization and Mapping that combines Python flexibility with C++ performance. It is a sparse SLAM implementation designed to map environment geometry and track device location by processing image frames into 3D points. The project features a bridge for exposing high-performance C++ classes to Python scripts using zero-copy memory sharing. This integration allows for switching between a scripting interface for rapid prototyping and a compiled core for execution speed. The system includes a spatial map optimizer to refine 3D point and camera pose estima

ORB_SLAM3 is a visual-inertial SLAM library designed for real-time simultaneous localization and mapping. It provides a framework for tracking camera movement and building 3D maps of environments using monocular, stereo, or RGB-D cameras combined with inertial sensors. The system features a multi-map fusion engine capable of merging separate spatial sessions into a single seamless representation of an environment. It includes specialized processing for wide-angle and fisheye lenses to expand the visual field of view for spatial tracking. The library covers a broad range of spatial intelligen

FAST-LIVO2 is a LiDAR-inertial odometry framework and factor-graph SLAM implementation designed for real-time robot localization and 3D mapping. It functions as a multi-sensor fusion pipeline and state estimator that integrates LiDAR, inertial, and camera inputs to track a robot's position and orientation. The system employs a tightly-coupled sensor fusion approach to maintain stable navigation, particularly in degraded environments. It utilizes a voxel-based 3D mapping tool to organize point clouds into volumetric grids, which optimizes memory usage and search speed during spatial reconstruc

VINS-Mono is a monocular visual-inertial odometry system and loop closure SLAM framework. It functions as a real-time state estimator that fuses data from a single camera and an inertial measurement unit to determine a robot's position and orientation. The project includes a non-linear optimizer for robotics and tools for sensor calibration. The system distinguishes itself through online sensor calibration, which automatically determines spatial extrinsics and temporal offsets between the camera and inertial unit during operation. It also incorporates rolling shutter distortion correction to

SpatialLM is a spatial modeling framework that uses large language models to transform monocular video and sensor data into structured indoor semantic maps. It functions as a system for indoor layout estimation and a point cloud semantic parser, converting raw geometric data into representations of architectural elements and object categories. The project aligns multi-modal sensor inputs with linguistic tokens, allowing a language model to serve as a reasoning engine for inferring room topology. It employs mechanisms to convert 3D point clouds and 2D image sequences into discrete tokens and s

ORB_SLAM2 is a visual simultaneous localization and mapping system that tracks camera movement and builds 3D environments from image data. It functions as a real-time visual odometry tool and sparse 3D reconstructor, computing the position and orientation of a camera while generating a point cloud map of a physical space. The system utilizes a camera relocalization engine to identify a camera's position within a known map after tracking failure or system restarts. It incorporates a spatial tracker to enable the precise insertion and composition of virtual 3D objects into real-world planar reg

Open_vins is a visual-inertial odometry framework and SLAM system designed for robotic state estimation. It uses an Extended Kalman Filter to fuse high-frequency inertial sensor data with visual feature tracks to estimate the position and orientation of a moving device. The system features a sensor calibration suite for calculating intrinsic and extrinsic parameters, as well as temporal offsets between cameras and inertial measurement units. It includes a manifold interpolator that uses B-Spline curves over the special Euclidean group to produce smooth trajectory paths between discrete pose e

Ceres Solver is a C++ library for numerical optimization, specializing in non-linear least squares and unconstrained optimization problems. It serves as a framework for automatic differentiation and robust curve fitting, providing tools to solve large-scale mathematical models. The library is distinguished by its bundle adjustment capabilities, which exploit sparse matrix structures to refine 3D scene points and camera parameters. It utilizes dual-number automatic differentiation to compute derivatives of cost functions, removing the need for manual Jacobian derivation. The project covers a

Autoware is a modular autonomous driving stack and open-source platform for advanced driver assistance systems. It functions as an integrated operating environment that manages the full pipeline from sensor data processing to vehicle actuation, utilizing the ROS 2 robotics framework for distributed communication and hardware abstraction. The system provides a comprehensive software architecture to enable autonomous driving across various vehicle platforms. It coordinates perception, planning, and control systems to operate vehicles without human intervention. The platform covers several core

BEVFormer is a perception framework that transforms multi-camera images into bird's-eye-view representations for autonomous driving. It functions as a multi-camera vision pipeline that integrates multiple camera streams into a single unified spatial perspective to facilitate environmental understanding. The system implements a transformer-based architecture that employs query-based feature extraction and spatiotemporal networks to aggregate spatial image features and temporal historical data. It uses recurrent temporal accumulation to maintain a persistent memory of the scene across consecuti

Slambook is a visual SLAM framework designed for simultaneous localization and mapping. It provides an integrated system to estimate camera motion and reconstruct 3D environments using visual sensor data. The project includes a visual odometry engine to track camera movement and a dense 3D reconstruction tool for creating volumetric representations of scenes. It features a loop closure detection system to recognize previously visited locations and a pose graph optimizer to refine trajectories and ensure global map consistency. The framework covers spatial estimation and environment modeling

Gyroflow is a gyroscope video stabilization software and IMU telemetry processor designed to remove camera shake from video files. It functions as a hardware-accelerated video renderer and lens calibration tool, utilizing embedded or external gyroscope and accelerometer data to perform pixel-level stabilization. The system is distinguished by its ability to integrate with professional non-linear video editing software via plugins, allowing stabilization to be applied directly to timelines without transcoding original footage. It supports diverse telemetry ingestion from camera brands, flight

VINS-Fusion is a multi-sensor fusion framework and visual-inertial odometry system. It integrates camera images, inertial measurement unit data, and global positioning signals through a non-linear optimization system to track the position and orientation of autonomous vehicles. The system includes a visual loop closure engine that utilizes a bag-of-words approach to recognize previously visited locations and correct trajectory drift. It further provides tools for online spatio-temporal calibration to determine the physical offset and time synchronization between cameras and inertial sensors d

ARKit-CoreLocation is a location integration framework designed to synchronize augmented reality scenes with real-world GPS coordinates. It provides a geospatial positioning engine and anchor system that links 3D scene objects to specific physical latitudes and longitudes. The framework distinguishes itself through sensor-fusion coordinate alignment, combining high-frequency motion data with GPS updates to maintain stable coordinates and refine user positioning. It includes specialized tools for compass calibration and scene orientation correction to align the 3D environment with True North.

Navigation2 is a ROS 2 navigation framework for autonomous mobile robots. It provides the core identity of a path planner, costmap management system, kinematic motion controller, and behavior tree orchestrator to compute collision-free routes and execute movement commands. The framework is distinguished by its use of behavior trees to coordinate modular task servers, enabling complex navigation routines and autonomous recovery actions. It supports a plugin-based architecture that allows planners and controllers to be swapped at runtime to adapt to different environments. The system covers a

PCDet is a LiDAR 3D object detection toolbox and point cloud processing library built on the PyTorch deep learning framework. It provides a system for identifying and locating three-dimensional objects within point cloud data. The project utilizes a data-model separation pattern to decouple dataset loading logic from the core detection pipeline. It features a multi-sensor fusion pipeline that combines data from multiple sensors into a shared spatial view and a distributed GPU training system to scale workloads across multiple graphics processors. The toolkit covers several capability areas,

Apollo is a comprehensive software stack designed for autonomous vehicle development, providing the necessary components for perception, planning, and control. It functions as a high-performance robotics middleware, utilizing a publish-subscribe data bus to facilitate low-latency communication between distributed modules and hardware sensors. The platform integrates data from cameras, lidar, and radar through a sensor fusion framework to generate a real-time environmental model for navigation. The system features a component-based runtime framework that manages task scheduling and resource al

PX4-Autopilot is a professional-grade flight control software stack designed for autonomous unmanned vehicles, including multicopters, fixed-wing aircraft, and vertical takeoff and landing platforms. It operates as a modular, real-time framework that decouples flight control logic from hardware drivers through a publish-subscribe middleware architecture. The system utilizes a deterministic microkernel runtime to execute time-critical flight control loops and sensor fusion tasks, ensuring stable navigation and vehicle operation. The platform distinguishes itself through a parameter-driven conf

Side-Menu.Android is a reusable UI component for Android applications that provides a slide-out navigation drawer. It is designed to help developers organize application sections and user options into a structured, hidden panel that maintains a clean interface for the primary content area. The component distinguishes itself through its visual presentation, which follows Material Design guidelines to ensure a consistent and intuitive user experience. It features a data-driven menu hierarchy that allows for logical grouping of navigation items, and it incorporates fluid circular reveal animatio

This project is a computer vision system for monocular depth estimation and 3D point cloud generation. It provides a supervised depth learning framework and a depth predictor capable of estimating spatial distance and disparity from single 2D images using pretrained neural networks. The system includes tools to transform 2D depth images into 3D point clouds via pixel coordinate backprojection and converts 3D point cloud data into 2D depth maps. It utilizes a training pipeline that supports model fine-tuning and hyperparameter optimization. The library covers broader capabilities in spatial a

Dummy-Robot is a software platform designed for the real-time teleoperation of desktop robotic arms. It functions as a human-robot interaction interface, translating gestural input and sensor data into fluid mechanical motion to enable remote physical task execution. The system utilizes a specialized control framework to map human hand movements directly to robotic actuators. By integrating sensor fusion and kinematic mapping, the software maintains low-latency synchronization between an operator's spatial inputs and the physical assembly, allowing for precise manipulation through a dedicated

PythonRobotics is a comprehensive collection of modular robotics algorithms and educational simulations designed for autonomous navigation, state estimation, and motion control. The project provides a library of standalone implementations for path planning, localization, mapping, and kinematics, serving as a resource for researchers and students to experiment with foundational and advanced robotic theories. The project distinguishes itself through an algorithm-centric design where each module functions as an isolated script, allowing for independent testing and clear pedagogical demonstration

Index repo for Kimera code