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.
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Updated
Oct 17, 2020 - Java
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.
Robotic Localization with SLAM on Raspberry Pi integrated with RP LIDAR A1. Point Cloud remote visualization doing using MQTT in real-time.
The official code and datasets for "Zero-Shot Multi-View Indoor Localization via Graph Location Networks" (ACMMM 2020)
Pose Correction for Highly Accurate Visual Localization in Large-scale Indoor Spaces (ICCV 2021)
Implementation of the paper Using Synthetic Data to Enhance the Accuracy of Fingerprint-Based Localization: A Deep Learning Approach (IEEE Sensors Letters, 2020), which utilizes Generative Adversarial Networks (GANs) for indoor localiztaion.
Library for Indoor Positioning purposes
Automated radio map construction using a Thymio II and a Software-Defined Radio (SDR)
Kindona is a flutter-based application for helping users orientate inside of buildings. It provides the user with a map (like google maps and the like), with the option to differentiate between the different floors inside the building.
Using WiFi signals (RSSI values) to predict indoor locations
Taha
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
The source files accompanying our research paper titled - "A Robust Approach for Improving the Accuracy of IMU based Indoor Mobile Robot Localization".
Autonomous Indoor Drone with Simulation and Hardware-Setup using ROS and SLAM
The scripts were intended to describe a Naive-Bayes-based approach to indoor location via WiFi signals.
Useful tools and software for high-precision positioning of low-cost smartphone
Indoor Localization via BLE Beacons: A Deep Learning Approach
POSTECH CSED499II Research Project II (지자기 지도 구축을 위한 지자기 데이터 수집 어플리케이션)
📌 An interdisciplinary team project of the course Software Lab at Technical University of Munich (TUM), aiming to map WiFi signals to increase localization accuracy with embedded IoT device ESP32 by tracking the position of nearby WiFi enabled devices.
Development and testing of an indoor positioning system using UWB
Source code for the paper "A Soft Range Limited K-Nearest Neighbors Algorithm for Indoor Localization Enhancement"
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