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Tags: Robotics
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1–24 of 26 · Most stars

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

  • lidar-odometry
  • lidar-slam
  • loam-velodyne
  • lidar-inertial

pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.

  • 3d-reconstruction
  • depth-prediction
  • feature-matching
  • global-features

An Efficient Probabilistic 3D Mapping Framework Based on Octrees. Contains the main OctoMap library, the viewer octovis, and dynamicEDT3D.

Build your own robot duck. XGO-Duck is a 3D-printable biped powered by Arduino UNO Q and 15 servos, adapted from Pollen Robotics' Microduck. Includes mechanical models, PCB designs, a BOM, and an assembly guide. Build it, explore its motion, and make it your own.

Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.

  • velodyne
  • ros
  • loam-velodyne
  • lidar

Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)

  • sensor-fusion
  • slam
  • mapping
  • icra2019

SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)

  • rangenet-lib
  • suma
  • lidar
  • slam

OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)

  • 3d-lidar
  • loop-closure-detection
  • slam
  • lidar

A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map.