3d-mapping

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

A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done in the Right Way https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/vizzo2023ral.pdf

[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.

LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.

A real-time, direct and tightly-coupled LiDAR-Inertial SLAM for high velocities with spinning LiDARs

Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking

A tool to automatically create 3D mappings of lights from two videos

Crafting 3D maps of Antarctica with PyGMT and the new IBCSO V2 data

Yahboom ROS Transbot Robot with Lidar Depth camera support MoveIt 3D mapping for Nvidia Jetson NANO 4GB B01

Implementation of 3D mapping using Kinect and RGB-D Camera sensors in an indoor environment. Real-time appearance-based mapping (RTAB-Map) was used to make the 3D map simulated in the Gazebo environment.

Adaptive graph-slam for rgbd cameras following a ransac-icp based estimator

3D mapping using Lidar TFmini. Softwares: matplotlib(python) / processing. Microprocessor: Wemos D1 mini / Atmega16 / Atmega32. Motors: stepper / servo. Motor driver: A4988.

The goal of this project is to build a robot capable of mapping its environment in a 3D simulation view. It uses a neural network for depth estimation deployed on a Jetson Nano. The Jetson is also connected to an Arduino Nano to get the gyro data from its IMU to project the depth values in a 3D world based on the orientation of the robot.

This is a online social robot navigation framework that implements several techniques for that matter, like the social relevance validity checking and an extended social comfort cost function.

A Cesium JS plugin that makes it easy to integrate Azure Maps services such as tile layers and geocoding services.

Implementation of VINS-Mono SLAM algorithm on NVIDIA Jetson TX1 to map a construction site and localize an aerial robot blimp.

This project provides an indoor localization system for visually impaired individuals.

Mapping and obstacles detection for unmanned underwater vehicles

This is a project where in an autonomous robot is built which makes use of the 3D mapping technique to map the entire environment and finally is able to navigate autonomously toward the detected switch board. This project was developed with the basic idea of making the robot to be able to navigate toward the switch board whenever it needs to be …