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Raw data simulation software SIMA
The raw data simulation software "SIMA" (Simulation of Multisensor Arrays) can be ued to validate and analyze navigation algorithms, as well as optimize them, under well-known and real conditions. The object's movement is defined from a trajectory, for example a circle, a rotation on the spot or as a waypoint definition, that can be imported from Google Earth.
SIMA enables the generation of raw data for:
- GNSS Pseudorange, Doppler and phase measurement observations,
- GNSS positions and velocity observations,
- observations of MEMS accelerometers and
- gyroscopes,
- magnetometer observations and
- inclinometer observations.
Output from SIMA includes a reference file with the complete and correct navigation state along the trajectory, and the observation files for each sensor, for example as RINEX file for GNSS or as a text file for the MEMS inertial sensors. These observation files can be used as input for the navigation algorithms to validate its solutions with the known reference.
Screenshot: Exemplary options and settings for the simulaion of GNSS raw data
Contact: Prof. R. Jäger, Email: reiner.jaeger@hs-karlsruhe.de
teXXmo Kaleo Georeferencer
Tablet PC with integrated 3D object geo reference sensors
Equipped with GNSS, the teXXmo-MEMS board and a laser distance measurement unit, the teXXmo KALEO.9A with 3D-Geoferencer can be used to measure 3D coordinate of objects for applications of facilty management, logistics and mobile GIS. Due to the distance measurement unit, indirect measurements can be performed.
More about the Kaleo Georeferencer: see specifications (german)
Contact: teXXmo GmbH, www.texxmo.de
Navka Virtual-Reality-Algorithms
Navka-Smartphone-Orientation-Algorithm: Video on Youtube
Orientation algorithm for Virtual-Reality-Applications:Video on Youtube
e-volo: manned multicopterWorld’s first manned flight with an electric multicopter |
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Navigation and control systems are being developed at the Hochschule Karlsruhe – Technik und Wirtschaft for a new kind of manned aircraft, a purely electrically powered vertical take-off and landing (VTOL) aircraft by the e-volo team. The project receives 2 Mio Euro federal funds.
Six consortium members (including the Institute of Applied Research (IAF) at the Hochschule Karlsruhe) are working on the new aircraft - the so called volocopter. The consortium receives about 2 Mio Euro in funding over the next three years.
Volocopter VC200 (Image: e-volo)
e-volo's volocopter is controlled by a pilot and has two seats. Unlike a traditional helicopter, the volocopter is powered by 18 rotors. Another difference is the energy source: the volocopter works with electric energy. This makes the aircraft silent, environmentally friendly and reduces flight costs. The batteries are laid out for a flight time of about an hour. With a total weight of 450 kg and a maximum altitude of 2000 m, the volocopter can reach a top speed of 100 km/h. It is also a very safe product: even with the failure of several motors, the volocopter can still land safely. For emergency situations there is a parachute installed. The volocopter has won the Charles Lindbergh 2012 award at the AERO aviation fair in Friedrichshafen, Germany.
Press release on November, 2011: Deutsch / Englisch Flyer: e-volo und Navka
Publication and discussion of the e-volo at IEEE Spectrum: http://spectrum.ieee.org/aerospace
More on www.e-volo.de
Photos: e-volo
e-volo
Syntern GmbH
Hirschstr. 91, 76137 Karlsruhe
www.e-volo.de
e-volo: manned multicopter |
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A new kind of navigation system is developed at the IAF for the aircraft with the following features:
- Deep coupling of raw sensor data.
- Sensor redundancy.
- Free leverarm and sensor-orientation design.
- Robust parameter estimation.
- On-the-fly and pre-calibration parametrization of the sensors.
- Coupled-georeferencing of external sensors (e.g. scanners and cameras for landing maneuvers and assistance).
NavLab - MATLAB basiertes Sensorframework zur Entwicklung von Navigationsalgorithmen
In der Forschung und Entwicklung von Navigationsalgorithmen werden je nach Anwendung und Szenario verschiedene Sensortypen miteinander fusioniert, um Position, Geschwindigkeit oder Orientierung von Objekten und Personen optimal zu schätzen.
Die Vorgehensweise bei der Entwicklung ist dabei unabhängig vom Szenario sehr ähnlich: Nach der Definition des mathematischen Modells muss die Datenaufnahme und Filterlogik implementiert werden. Das Ergebnis wird dann mit einer Referenzlösung verglichen. Hierbei fällt zwischen den Entwicklern viel redundante Arbeit an; oft werden auch verschiedene Standards und Datenstrukturen definiert, die zwar für sich eine gute Lösung darstellen, aber oft nicht flexibel genug sind um von anderen algorithmischen Weiterentwicklungen zu profitieren. Um dies zu vermeiden wird im Rahmen des FuE-Projekts NAVKA das MATLAB basierte Sensorframework NavLab entwickelt. Das NavLab-Framework bietet einen einheitlichen und erweiterbaren Rahmen zur Standardisierung der Datenstrukturen, Zustandsschätzerlogik und der Visualisierungskomponenten.
- Standardisierte Datenstrukturen und Schnittstellen für Sensorbeobachtungen im Postprocessing (SIMA-Format)
- Standardisierte Definitionen für Initialisierungswerte, Varianzen, Lever-Arm-Parameter, ect.
- Standardisierte Zustandsschätzerlogik (Filter)
- Standardisierte Beobachtungsgleichungen z.B. für Positions-, Geschwindigkeits-, Orientierungs- und Automotive-Mode-Beobachtungen unter Berücksichtigung der Lever-Arme
- UDP-Schnittstellen für Beobachtungsdateninput und Ergebnisausgabe
Automatisierte Speicherung der Beobachtungs- und Zustandshistory
- Simulation bzw. Berücksichtigung von Zeitverzögerungen in den Beobachtungen
- De/-Aktivierung von einzelnen Sensoren und Sensorgruppen
- Standardisierte Visualisierung im Postprocessing
- Bereitstellung von Basisfunktionalität wie
- Schwere- & Magnetfeldmodelle
- Referenzellipsoidparameter
- Koordinatentransformation
- Quaternionenfunktionen
Welcome at Navigation Algorithms and Platforms Karlsruhe (NAVKA)
NAVKA is settled at the Institute of Applied Research (IAF) of the Karlsruhe University of Applied Sciences (HSKA) as RaD project on the following subjects
- Algorithms and optimum design for hybrid multi-sensor platforms for seamless out-/indoor navigation
- Algorithms and design for hybrid geo-referencing of objects
- Algorithms for GNSS-based positioning and navigation applications
