Strongly accurate indoor positioning algorithms with the main focus on indoor navigation developed by Navigine company. Here we will step by step publish the source code of our algorithm starting with trilateration.

[Esri GIS 2nd Prize] We developed this indoor and outdoor seamless positioning and navigation system under the Android system by using the built-in multi-sensors of mobile phones.

Topological Semantic Graph Memory for Image Goal Navigation (CoRL 2022 oral)

AR app for indoor navigation using ARcore and Sceneform.

[ICCV 2021] Official implementation of "The Surprising Effectiveness of Visual Odometry Techniques for Embodied PointGoal Navigation"

Robotic Localization with SLAM on Raspberry Pi integrated with RP LIDAR A1. Point Cloud remote visualization doing using MQTT in real-time.

Source code for M.T. Hoang, B. Yuen, X. Dong, T. Lu, R. Westendorp and K. Reddy, “Recurrent Neural Networks for Accurate RSSI Indoor Localization,” IEEE Internet of Things Journal, 2019

[ICCV 2023] PEANUT: Predicting and Navigating to Unseen Targets

An indoor positioning system (IPS) is a system to locate objects or people inside a building using radio waves, magnetic fields, acoustic signals, or other sensory information.

Library for Indoor Positioning purposes

Augmented Reality for Indoor Navigation System - An Android application for navigating user in an indoor environment with augmented arrows, without continuous data connectivity. For initial development work of project refer link

Interactive SVG map with indoor wayfinding powered by React

[ECCV 2024 Oral] SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments

Library for low-cost navigation of small/IoT devices

The MapsIndoors SDK is the idea of integrating everything on your venue, like people, goods, offices, shops, rooms and buildings with the mapping and wayfinding technologies provided in the MapsIndoors platform. The easiest way to test this out is by running 'pod try MapsIndoors' using CocoaPods.

This system provides service for navigation inside buildings with some functions like Find way inside a building and navigate user in a building using QRCode and Augmented Reality using ARCore and Azure Spatial Anchor.

This is an open-source project that employs deep learning to enhance indoor positioning using WiFi Channel State Information (CSI). This project aims to harness the detailed data from CSI, such as signal amplitude, phase, and environmental properties, to accurately locate devices inside buildings where GPS is ineffective.

indoor segmentation - indoor semantic segmentation Android using Deeplabv3 MobileNetV2 trained with ADE20K dataset

SDK for iOS to develop own indoor navigation apps, and Navigine demo application for iOS to test indoor navigation. Now you get one code for all types of devices with less resource use.

Source code for the paper "A Soft Range Limited K-Nearest Neighbors Algorithm for Indoor Localization Enhancement"