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* Einladung

* Informatik-Oberseminar

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Zeit: Mittwoch, 5. Mai 2021, 11.00 Uhr

Ort: Videokonferenz (Zoom-Meeting, Information siehe unten)

Referent: Martin Schweigler, M.Sc. RWTH

Informatik 11 - Embedded Software

Thema: Ground Surface Pattern Recognition for Enhanced Navigation

Abstract:

With the continuous increase in sales of electrical assisted bicycles over the last decade, the

number of bicycle accidents across Europe has simultaneously grown significantly. At the

same time the technology lacks on active safety systems, even though the electrification

of the so-called Pedelecs would allow their development. This dissertation can be seen as

the first step in the process of developing position and situation dependent active safety

systems by improving the position determination accuracy of bicycle navigation systems.

In the core of this work a position estimation system is developed, which uses road

sections with significant surface conditions to improve the positioning accuracy of a

conventional GNSS/INS. Based on the vertical accelerations acting on the moving Pedelec,

the system recognizes individual spots in the road surface, e.g. manholes or potholes. To

be more precise, the individual acceleration profiles that occur when passing different

spots, are recorded with a smartphone and statistically modeled offline with the help of

continuous hidden Markov models during the training phase. In online mode, the trained

models are then used to recognize the spots by the acceleration profiles of the revisited

road sections. The absolute positions of the Pedelec, relative to the global coordinates

of the recognized spots, are subsequently determined by an inertial calculation of the

distances traveled in the time between their detection and classification. The system thus

uses statistical models to estimate the absolute position of the Pedelec and is consequently

called Statistical Absolute Position Estimator, or SAPE.

In the second part of this work, SAPE is used to develop a navigation system, which

shows the potential of the ground surface pattern recognition. For this purpose the SAPE

and GNSS position determinations are fused with an inertial navigation system using an

extended Kalman filter. Since the inertial sensors provided by the chosen smartphone

are not accurate enough to realize a stand-alone INS, an odometry is developed and

implemented to support the navigation solution. The resulting GNSS, SAPE and

odometry supported INS is finally evaluated using an RTK GNSS and its accuracy is

compared to that of a conventional odometry supported GNSS/INS created with the

same low-cost hardware.

Es laden ein: die Dozentinnen und Dozenten der Informatik

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Thema: Promotionsvortrag Martin Schweigler

Uhrzeit: 05. Mai 2021 11:00 AM Amsterdam, Berlin, Stockholm, Wien

Zoom-Meeting beitreten

Meeting-ID: 963 2533 4175

Kenncode: 988764