Research and Development Projects with Public Funding

MSFUSION

Next Generation Motion Sensors for Hybrid GNSS/INS Solutions in high accuracy machine control applications

 

Project Overview: 

The objective of MSFUSION was to prove new low-cost motion and positioning multi-sensor technologies based on the exploitation of advanced calibration and sensor fusion techniques (including those using Artificial Intelligence/Machine Learning) in order to improve the overall PNT performance experienced by the user, especially in GNSS degraded environments ((indoor, outdoor and mixed scenarios) which can be found in some industrial applications. These include cases with temporal GNSS outages, low number of visible satellites (e.g. 1, 2 or 3 satellites) and strong multipath/NLOS conditions. The objective is to improve the PNT performance in terms of availability and accuracy at a low cost.

 

Project Objectives 

The MSFUSION project aims to develop a set of bread boards for a car and a human operator with advanced localisation algorithms from multiple sensors that are fused to provide an accurate and reliable positioning solution across a diverse set of use cases that encompass almost all major challenges.

  • Adaptive techniques (including those using Artificial Intelligence/Machine Learning) for adaptively tuning the sensor fusion algorithms.
  • Architectures and techniques (including those using Artificial Intelligence/Machine Learning) exploiting clusters of multiple low-cost sensors of the same type (e.g. multi-IMU systems) so that the error of the combined measurement (and associated drift for dead-reckoning techniques) is reduced with respect to the individual sensors.
  • Use of stable timing references (e.g. Miniaturized Atomic Clocks) for improved PNT performance.
  • Tightly coupled multi-sensor techniques to improve the convergence time of PPP algorithms and the availability of accurate PNT (considering at least the case of floating ambiguities).
  • Integration of multiple heterogeneous sensors including odometer, , visual camera, ranging sensors (e.g. LiDAR, Time-of-Flight), IMUs and multi-GNSS receiver.

 

Intel Labs Project SafeAdArchitect

Project period:
09/2021 – 01/2024

Project partners:
SpaceApplications

Project leader:
Jorge Moran Garcia, ANavS GmbH

Funded by:
ESA

HAS PHASE 2

Enabling Ultra High Accuracy Positioning with advanced correction services

 

Objective(s) of the Project: 

The activity will investigate, develop, and demonstrate innovative GNSS PPP-RTK positioning algorithms suitable for real-time high accuracy positioning with State Space Representation (SSR) GNSS corrections coming from the Galileo High Accuracy Service (HAS) and other experimental sets of corrections, validated against other sources of SSR corrections like CNES IGS real-time correction dissemination. 

Innovation shall primarily focus on advanced signal filtering techniques for GNSS measurements up to 3 or 4 frequencies to enable robust carrier ambiguity resolution exploiting real-time high accuracy SSR corrections for PPP-RTK, including the application of orbits, clock, biases, ionosphere corrections and their variance-covariance matrix. 

 

The following objectives are to be achieved: 

  • Identify the relevant algorithms for high accuracy positioning with SSR set of corrections, principally focusing on the corrections provided by the Galileo HAS in Phase 1 and its evolutions for Phase 2.
  • Define and develop techniques for exploiting ambiguity resolution, ionosphereweighting modelling, and correction accuracy indication for static and kinematic users, taking into account all the necessary metadata collection and pre-processing steps for performing navigation data (PVT) computation with the highest accuracy achievable by
    a determined set of SSR corrections.
  • Develop a system for collecting the necessary real data (triple or quadruple frequency GNSS signals, assistance, and corrections data, etc.) and performing all the functions and algorithms involved in the above innovations up to the sequential estimation of the user state vector.
  • Test of the developed system in field trials representative of the identified use cases (real collected data) and compare the obtained performances against available solutions and references trajectories.

The task of ANavS within the project is to provide the ANavS SW to design, develop and verify innovative GNSS PPP-RTK positioning algorithms suitable for real-time high accuracy positioning with State Space Representation (SSR) GNSS corrections.   

 

Intel Labs Project SafeAdArchitect

Project period:
01/2024 – 12/2024

Project partners:
ANavS GmbH

Project leader:
Philipp Bohlig, ANavS GmbH

Funded by:
ESA

DREAM 

Driving Aids powered by E-GNSS and machine learning

 

The aim of the DREAM project (Driving-aids powered by E-GNSS, AI & Machine Learning) is to design, build and demonstrate a HW- and SW-prototype in an operational environment. This will utilise the unique differentiators of Galileo, such as the High Accuracy Service and innovative artificial intelligence/machine learning techniques.

The target application of this HW and SW prototype is “Driving aids for buses”. The applications aim to support the driver in driving safely by providing him with safety-relevant information based not only on the vehicle position and dynamics, but also on the environment. Specifically, the aim is to provide highly accurate and reliable information that warns the driver, for example, about running a red light, speeding, avoiding collisions/accidents or driving the wrong way.

This means that the ultimate goal is not to develop the ADAS system itself, but to provide the necessary position-, speed-, attitude- and environment-related information to support these types of applications.

The task of ANavS is to increase the reliability of GNSS positioning and maintain accuracy even in times when the GNSS signal is lost. In addition, the surrounding objects must be localised and the necessary measures taken to avoid collisions and accidents.

Intel Labs Project SafeAdArchitect

Project period:
12/2023 – 11/2025

Project partners:
ANavS GmbH

Project leader:
Jorge Moran Garcia, ANavS GmbH

Coordinated by:
EUSPA (European Union Agency for the Space Program)

Funded by:
European Commission

ESA Nav 4 Future Mobility NAVISP Project

We are participating in the NAVISP Element 2 programme of the European Space Agency (ESA) as a subcontractor of DiMOS Operations GmbH. This project aims to strengthen the competitiveness of the PNT industry.

According to the German law on automated driving, which will also be transposed into European law from 2022, a technical monitoring service is required for highly automated vehicles in public transport and logistics to ensure safety.

As part of the ESA Nav 4 Future Mobility NAVISP project, DiMOS and we as a subcontractor are working together with the Ostbayerische Technische Hochschule Regensburg on the development of a “demonstrator for a technical monitoring service”. This demonstrator will demonstrate continuous monitoring of navigation performance for safety-critical applications using GNSS and LEO-PNT signals. The project was successfully launched in September 2023.

Intel Labs Project SafeAdArchitect

Project period:
09/2023 – 02/2025

Project partners:
– ANavS GmbH
– Ostbayerische Technische Hochschule Regensburg

Project leader (at ANavS):
Andreas Sperl, ANavS GmbH

Coordinated by:
DiMOS Operations GmbH

Funded by:
European Space Agency (ESA)

x-in-a-Box

The accurate recording of construction and maintenance work carried out on the track is an important prerequisite for the introduction of predictive maintenance management at the Swiss Federal Railways (SBB).  

In the past, this work was reported on paper. This manual method is inefficient, error-prone and also represents a media disruption. Furthermore, the data cannot be processed automatically in this form.  

 As part of the “X-in-a-Box” project, ANavS GmbH was commissioned together with the Rhomberg Sersa Rail Group to develop a mobile positioning system (mPOM) for track maintenance machines and to integrate it into the existing SBB IT system landscape.   

With the introduction of this mobile tracking system, including the recognition of work assignments for track maintenance machines, their work performance is automatically recognised, located and made available for further processing.  

 By eliminating manual recording, media disruptions and potential sources of error are reduced.  

In addition, the quality of the suppliers’ workmanship can be better assessed on the basis of the consistently and digitally recorded work performance.   

Our multi-sensor RTK module, which already contains a fusion of GNSS, IMU and odometry data and thus enables a position accuracy of 1 cm under favourable GNSS conditions and better than 1 m in certain sections without GNSS reception, is to be used as the starting point for the development. 

Intel Labs Project SafeAdArchitect

Customer:
Schweizer Bundesbahn (SBB)

Project period:
10/2023 – 12/2024

Project partners:
– ANavS GmbH
– sersa – Rhomberg Sersa Rail Group

Project leader (at ANavS):
Andreas Sperl,  ANavS GmbH

Coordinated by:
SBB Infrastruktur

ABSOLUT II

 

  • The Federal Ministry for Economic Affairs and Climate Protection (BMWK) is funding the continuation of the ABSOLUT research and development project.
  • The second phase, which is now starting, aims to build on the successful results of the previous project and realise further steps towards later regular operation.
  • The project launch will take place on 13 November 2023, from 10:30 a.m. to 12 noon, at the Institute of Wood Technology Dresden, Zellescher Weg 24, 01217 Dresden.

“With the technology programme “Information and Communication Technologies (ICT) for Electromobility”, the federal government is promoting key technologies for the upcoming challenges of the energy and transport transition. With ABSOLUT II, we are continuing the success story of the Central German partner consortium in order to drive forward local public transport as a whole with the help of digitalisation,” says Christian Liebich, project manager of the “ICT for electromobility” technology programme at BMWK.

While the predecessor project ABSOLUT developed and built the overall system of a highly automated, demand-driven public transport landscape and evaluated it by means of trials with test persons, ABSOLUT II now aims to solve a central problem: The existing safety driver in the vehicle is to be replaced by a stationary technical supervisor in a control centre, in accordance with the law on autonomous driving, thus enabling remote vehicle access. All interfaces between the system components are to be developed with the partners in the project on a manufacturer-neutral and open basis.

“The overall objective of the ABSOLUT project is in line with the city of Leipzig’s mobility strategy, which aims to strengthen sustainable mobility. The standardised provision of data from the city can make a significant contribution to the automation of transport in public spaces,” says Michael Jana, Head of the City of Leipzig’s Transport and Civil Engineering Department.

In the follow-up project, a total of 10 partners from industry, local authorities and research are working on a technical solution which, when completed, will enable several vehicles to be managed by one employee, thus opening up real scaling potential. Leipziger Verkehrsbetriebe is acting as consortium leader and is pooling the work of Advanced Navigation Solutions – ANavS GmbH, BitCtrl Systems GmbH, FSD – Zentrale Stelle, glts cotech GmbH, IKEM – Institut für Klimaschutz, Energie und Mobilität, INIT GmbH, Sedenius Engineering GmbH, the City of Leipzig and Dresden University of Technology. Other associated partners are Leipziger Messe and BMW Group Plant Leipzig.

“By bundling innovations, we want to provide further impetus for the business location, generate digitalisation knowledge and innovations for local public transport and thus help shape the future of public mobility,” says Ulf Middelberg, CEO of Leipziger Verkehrsbetriebe.

The ABSOLUT II project will run until 2026 and has a total volume of around 12 million euros. The project is being funded by the Federal Ministry for Economic Affairs and Climate Protection on the basis of a decision by the German Bundestag.

You can find more information at www.absolut-projekt.de or on the L-Blog at www.L.de.

Intel Labs Project SafeAdArchitect

RepliCar

  • Development of a high-precision reference system for environment recognition for automated driving
  • Sensor fusion of high-resolution radar, camera and lidar data
  • Development of innovative test procedures and methods

 

Safe perception of the environment is a crucial prerequisite for automated driving. The sensors and processing chains used must fulfil the highest requirements in terms of reliability, precision and fidelity to reality. There are currently no approaches for the effective and efficient validation of sensors and processing chains. The joint project RepliCar closes this gap: the aim of the project is to develop a reference system with integrated high-resolution radar, camera, lidar, GNSS and inertial sensors and to integrate it into a test vehicle.

This reference sensor system will be several years ahead of today’s series sensor technology. The integration of particularly high-resolution sensors and a particularly powerful sensor data fusion for object recognition make it possible to determine a highly accurate representation of reality, a so-called “ground truth”. This forms the basis for validating sensors for automated driving.

The consortium leader is ANavS GmbH, Munich. This company is also developing the sensor data fusion for determining the “ground truth” for self-localisation and environment perception. The Institute for High Frequency Technology and Electronics (IHE) at the Karlsruhe Institute of Technology (KIT), Offenburg University of Applied Sciences (HSO) and Freudenberg FST GmbH, based in Weinheim, are developing a high-precision radar system. This is an essential element in the reference system for environment perception and is described in intervals by the Institute for Regulation and Control Systems (IRS) at KIT. The project partners Akkodis Germany GmbH, Sindelfingen, the FZI Research Centre for Information Technology, Karlsruhe, IAVF Antriebstechnik GmbH, Karlsruhe, IPG Automotive GmbH, Karlsruhe, and GTÜ Gesellschaft für Technische Überwachung mbH, Stuttgart, define and implement all steps from the simulative validation to the release of the sensors and functions. The individual innovations in the validation and testing process for series sensors include artificial intelligence methods for analysing recorded scenarios, a “sensor in the loop” test bench, integration into existing simulation tools and a modular verification and validation process. The other partners HighQSoft GmbH, Idstein, and RA Consulting GmbH, Bruchsal, are building a powerful data platform for managing, processing and providing the reference data. The driving demonstrator is being realised by Dr. Ing. h.c. F. Porsche AG, Stuttgart, is realising the driving demonstrator. It records initial data and uses it for the approval process of an exemplary perception system.

You can find more information at: www.replicar-project.de

Intel Labs Project SafeAdArchitect

Floow

Autonomous cargo systems in factory transport

The FLOOW research project aims to develop new solutions for the mobility of people and transported goods with a focus on factory transport.

MOTIVATION

The trend towards urbanisation has been continuing worldwide for decades. More than a third of the population now lives in densely populated regions, which means that living and parking space is becoming increasingly scarce. Commuter flows and inner-city traffic are leading to massive congestion of the infrastructure and a shortage of transport space. What is needed is an alternative to journeys by private motorised transport that can compete with the comfort of owner-occupied cars, while at the same time significantly reducing the need for vehicles and the amount of space used per vehicle. The aim of the FLOOW joint project is to close this gap and demonstrate it on a closed test site.

SOLUTION APPROACH

The FLOOW project utilises the key advantages of artificial intelligence (AI) to create new solutions for the mobility of people and goods. These relate in particular to the robust and highly accurate localisation of mobility systems (indoor and outdoor), generalised environment recognition and risk-aware manoeuvre planning on dedicated hardware for the energy-efficient solution of complex sub-problems on vehicles. This addresses indoor and outdoor use as well as combined use with transition between the two areas. An automated guided vehicle system (AGV), an automated cargo bike and a cargo mover serve as exemplary vehicle platforms. The final integration of the prototypes into an overall mobility system with intelligent fleet utilisation on a factory site represents an exemplary implementation for urban use when ready for the market.

More Information: www.floow-project.de

Intel Labs Project SafeAdArchitect

SafeADArchitect

In the current world of automated vehicles (AVs), the primary goal is to achieve high safety, while often sacrificing usability. In particular in urban environments, human intervention is often required to maneuver the AV out of a situation. The reasons for the urban challenges are manifold and include high levels of occlusion and a high degree of uncertainty for the behavior of other traffic participants. To address these challenges, a consortium consisting of Intel Deutschland GmbH (Intel Germany), Schaeffler Technologies AG & Co. KG, Karlsruhe Institute of Technology (KIT), FZI Forschungszentrum Informatik, ANavS GmbH, Lake Fusion Technologies GmbH (LFT) and Ibeo Automotive Systems GmbH submitted the joined research proposal “SafeADArchitect”, which now received the funding approval from the German Ministry for Economic Affairs and Energy, and will be funded for the next 2.5 years.

The goal of the “SafeADArchitect” project is to develop new approaches and concepts to improve safety of automated vehicles in urban environments. For this purpose, new methods that enable realtime monitoring and mitigation of risks (e.g. collision risk, risk of control loss, etc.) will be in focus. In this regard, it is a primary goal of “SafeADArchitect” to develop a comprehensive architecture solution including necessary safety layers covering the complete system. This means that not only the main software components of the AV are included in this study, but also the computing hardware itself, the necessary sensors and even the driving platform will be considered. In addition, new ways to facility the certification process for functional safety standards such as the ISO-26262 will be investigated.

ANavS® will be responsible for the Multi-Sensor Localization in “SafeADArchitect”. This means that ANavS® will develop a safety concept for its localization and integrate it into its positioning systems. Moreover, ANavS® will provide its Multi-Sensor RTK module for the test vehicles of Schaeffler.

The project “SafeADArchitect” will lead to a new generation of positioning systems and, thereby, strengthen the position of ANavS® in the automotive market.

Learn more

Intel Labs Project SafeAdArchitect

Project key numbers:

Project period:
11/2020 – 03/2023

Project partners:
ANavS GmbH
Schaeffler Technologies AG & Co. KG
LAKE FUSION Technologies
Forschungszentrum Informatik (FZI)
Karlsruher Institut of Technology (KIT)
Intel Deutschland GmbH

Project leader (at ANavS):
Dr. Patrick Henkel, ANavS GmbH

Associated partner:
Ibeo Automotive Systems GmbH

Coordinated by:
Intel Deutschland GmbH

Funded by:
German Federal Ministry for Economic Affairs and Energy (BMWi)

VorSAFe-Plus

A predictive safety system for autonomous driving will be developed in “VorSAFe-Plus”. Project partners include BMW as vehicle manufacturer and Continental, ANavS, AKKA and ADC Automotive Distance Control Systems as automotive suppliers and development partners.

The project “VorSAFe-Plus” shall enable a wider use of the vehicle’s interior of automated vehicles. Therefore, additional safety systems for pre-crash detection, active safety functions such as Emergency Steer Assist for minimization the crash severity, and extended passive safety concepts with variable “smart” airbag systems shall be explored.

ANavS® will be responsible in “VorSAFe-Plus” for the precise localization of the test vehicle. This includes the exploration of radar technologies to support the localization and the integration of new Simultaneous Localization and Mapping (SLAM) algorithms using camera and LiDAR measurements into the ANavS® sensor fusion. ANavS® will also provide its RTCM reference station and its Multi-Sensor RTK module for the test vehicle. The project will lead to a new generation of positioning systems and strengthen the position of ANavS® in the automotive market.

Link to further press release:
https://www.stmwi.bayern.de/presse/pressemeldungen/pressemeldung/pm/21-2021/

Project key numbers:

Project acronym:
VorSAFe-Plus

Project title:
Vorausschauende Sicherheitssysteme für das automatisierte Fahren – Forschung im Fahrzeug

Project period:
01.12.2020 – 30.11.2023

Project partners:
ANavS GmbH, Munich
BMW AG, Munich
Continental Automotive GmbH, Regensburg
AKKA DSO GmbH, Munich
Automotive Distance Control Systems GmbH (ADC), Lindau (Bodensee)
Technische Hochschule Ingolstadt (THI), Ingolstadt                                         

Project leader:
Technische Hochschule Ingolstadt (THI), Ingolstadt

Funded by:
Bavarian Ministry of Economic Affairs, Regional Development and Energy
(BayVFP Förderlinie Digitalisierung, Informations- und Kommunikationstechnologie)

KI-NAVI

Background:
Autonomous driving requires precise and reliable position information. This can only be achieved by using multiple complementary and redundant sensors, e.g. Global Navigation Satellite System (GNSS) receivers, inertial sensors, wheel odometry, camera, radar or Lidar. Obviously, there is a need for a sophisticated sensor fusion.

Project topic:
The goal of KI-NAVI is the development of an AI-aided high-precision positioning system with a powerful sensor fusion for autonomous driving. Conventional positioning techniques such as Real-Time Kinematic (RTK) positioning and Kalman filter-based sensor fusion shall be enhanced by camera and 3D Lidar data. A very important part of the project will be the integration of newest Artificial Intelligence (AI) algorithms for three objectives:

– Determination of motion information by AI-based Lidar/ visual odometry
– Determination of 3D maps with semantic information
– Monitory of functional safety

The sensor fusion architecture of KI-NAVI is shown below. The positioning system includes an ANavS® Multi-Sensor RTK module (with 3 embedded Multi-frequency, Multi-GNSS receivers, an inertial sensor and a CAN interface for wheel odometry), a 3D Lidar, a stereo camera and a powerful processing architecture.

Link to the official BMBF project page:
KI-gestützte Lokalisierung autonomer Fahrzeuge mittels Sensordatenfusion

Sensor fusion for position determination with integration of Lidar, camera and vehicle data (highlighted in orange) into ANavS Multi-Sensor RTK positioning, aided by AI components (highlighted in blue)

Project key numbers:

Project period:
01.09.2019 – 31.08.2022

Project partners:
ANavS GmbH
Technische Universität München (TUM)
3D Mapping Solutions GmbH

Project leader:
Dr. Patrick Henkel, ANavS GmbH

 

Funded by:
German Federal Ministry of Education and Research (BMBF)

Logo - gefördert vom Bundesministerium für Bildung und Forschung
KI NAVI Logo

OPA3L

Background:
The goal of the research project “Optimal Assisted, highly Automatized, Autonomous and Cooperative Vehicle Localization and Navigation” (OPA3L) is the automation of recurring car drives in a known environment and the development of solutions for cooperative maneuvers in these areas.

Project contribution of ANavS®:
ANavS® contributes to the project with the development of a multi-sensor localization. Important steps will the development of new algorithms for monitoring the integrity of the sensor fusion or the integration of a Lidar Simultaneous Localization and Mapping (SLAM) algorithm into its Multi-Sensor, Multi-frequency RTK positioning. The test vehicles of IAV will also be equipped with the Multi-Sensor RTK positioning modules of ANavS®.

Project key numbers:

Project period:
01.03.2019 – 14.02.2023

Project partners:
Universität Bremen, 
IAV GmbH, Chemnitz
Universität der Bundeswehr, Neubiberg
ANavS GmbH, München

Project leader (at ANavS):
Dr. Patrick Henkel, ANavS GmbH

Funded by:
German Federal Ministry for Economic Affairs and Energy (BMWi)

Prepare Ships

Prepare Ships is creating a smart positioning solution by developing and demonstrating a data fusion of different sensor and signal sources to enable a robust navigation application. The idea is that vessels with accurate positioning based on EGNSS, data and machine-learning should be able to predict future positions of nearby vessels. Besides a decreased risk for collisions, this also means additional benefits in the form of a more energy effective manoeuvring of the vessels, something which can also reduce the environmental impact of shipping in line with IMO’s targets.

Link to official project website: Prepare Ships

Project key numbers:

Project period:
01.12.2019 – 31.01.2022

Project partners:
RISE – Research Institutes of Sweden
SAAB, Sweden
Telko, Norway
ANavS GmbH, Germany
Lantmäteriet, Sweden

Project leader (at ANavS):
Dr. Patrick Henkel, ANavS GmbH

Funded by:
European GNSS Agency,
H2020-SPACE-EGNSS-2019-2020

PoK-UVM

PoK-UVM is an R&D project co-funded by the Bavarian Ministry of Economic Affairs, Regional Development and Energy. It aims at developing technologies for safe integration of drones into future UAS Traffic Management Systems (UTM / U-Space). ANavS® contributes to the project with a resilient positioning system that integrates position information obtained from satellite communication systems (e.g. Iridium) into its Multi-Sensor RTK positioning modules.

Publication of ANavS® related to scope of project:
Precise 6D RTK Positioning System for UAV-based Near-Field Antenna Measurements

Further project information

Project key numbers:

Project period:
01.12.2018 – 30.11.2021

Project partners:
esc Aerospace GmbH, Taufkirchen
ANavS GmbH, Germany

Project leader (at ANavS):
Dr. Patrick Henkel, ANavS GmbH

Funded by:
Bavarian Ministry of Economic Affairs, Regional Development and Energy
Informations- und Kommunikationstechnik (IuK-Programm)

ESA Logo

NAVISP-EL1-026 is an R&D project funded by the European Space Agency (ESA) with the goal to enable ultra-high accuracy positioning in challanging environments.
The need for high accuracy PNT in challenging environments has become obvious and, henceforth, mandatory for many applications. Currently, an accuracy target of 1 m in an urban environment seems a realistic achievement with multi-GNSS PPP or RTK capabilities. A significant R&D effort is ongoing to reach this target in operational products, using carrier phase positioning (PPP and RTK) and European institutions are actively taking their part in this effort.
In most hybrid PNT systems, GNSS is rightly considered the primary source of high-accuracy positioning, including in urban environments. Hence, current techniques and R&D efforts rely on GNSS as the primary source of high accuracy for both absolute and relative positioning.
Learn more