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Getting StartedExamplesAPI

This repository contains the core component for OpenHPS (Open Source Hybrid Positioning System). It includes concepts for creating the model, nodes and data object definitions.

OpenHPS is a data processing positioning framework. It is designed to support many different use cases ranging from simple positioning such as detecting the position of a pawn on a chessboard using RFID, to indoor positioning methods using multiple cameras.


  • 2D, 3D and Geographical positioning.
  • Relative positioning.
  • Basic positioning algorithms (e.g. trilateration, triangulation, fingerprinting, dead reckoning...)
  • Advanced positioning algorithms (e.g. computer vision through @openhps/opencv)
  • Extremely extensible.
  • Open source.


Positioning Algorithms

  • @openhps/imu - Adds IMU processing nodes for fusing IMU sensors.
  • @openhps/rf - Adds RF processing nodes and data objects.
  • @openhps/fingerprinting - Adds various fingerprinting nodes and services for offline and offline positioning models.
  • @openhps/video - Provides general data objects and data frames for working with images, video data or cameras.
  • @openhps/opencv - Provides linkage with opencv4nodejs and OpenCV.js for computer vision algorithms on the server or browser.
  • @openhps/openvslam - Provides bindings to OpenVSLAM
  • @openhps/orb-slam3 - Provides bindings to ORB-SLAM3


  • @openhps/geospatial - Enables the concept of geospatial spaces (e.g. building, room) on top of reference spaces.

Data Services


  • @openhps/socket - Provides node communication through Socket.IO for remote models.
  • @openhps/rest - Provides node communication through restful endpoints.
  • @openhps/mqtt - MQTT client node communication and standalone MQTT server.



  • @openhps/sphero - Example implementation for controlling and receiving sensor data from Sphero toys.
  • @openhps/csv - Read and write data frames from/to CSV files.

Getting Started

If you have npm installed, start using @openhps/core with the following command.

npm install @openhps/core --save

The core idea and goals of OpenHPS are outlined in the technical paper: OpenHPS: An Open Source Hybrid Positioning System.


import { ModelBuilder } from '@openhps/core';

.build().then(model => {
// ...


  • openhps-core.js: UMD
  • openhps-core.es.js: ES6 import
  • worker.openhps-core.js: UMD worker
  • openhps-core-lite.js: UMD lite version for embedded systems


The framework is open source and is mainly developed by PhD Student Maxim Van de Wynckel as part of his research towards Hybrid Positioning and Interoperable Positioning Systems under the supervision of Prof. Dr. Beat Signer.


Use of OpenHPS, contributions and feedback is highly appreciated. Please read our contributing guidelines for more information.


Copyright (C) 2019-2024 Maxim Van de Wynckel & Vrije Universiteit Brussel

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at


Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.