German Aerospace Center (DLR) - UPM · Railway Collision Avoidance Relative Positioning Pedestrian & Vehicular Navigation 40 employees: 19 PhD students, 17 PhD scientists, 2 technicians,

German Aerospace Center

(DLR)

Alberto Viseras Ruiz

Who I am…

www.DLR.de • Chart 2 > Alberto Viseras Ruiz • Presentation DLR > 23 January 2015

Alberto Viseras Ruiz:

o Telecommunications Engineer UMA.

o Research intern at Sony Deutschland

GmbH, Stuttgart.

o Master Thesis at German Aerospace

Center (DLR).

o Working at DLR since October, 2013.

Agenda

1. Research Institutions in Germany

2. German Aerospace Center (DLR)

3. Communications Systems Department

4. Master Thesis‘ Topics

5. Career Opportunities. How can I join DLR?


Research Institutions in Germany


Max Planck German Aerospace

Center Fraunhofer

Juan Ignacio Cirac Pedro Duque

www.DLR.de > Institute of Communications and Navigation > Department Communications Systems > Uwe-Carsten Fiebig et al. > January 2015 > Slide No. 5

n Cologne

n Oberpfaffenhofen

Braunschweig n

n Goettingen

Berlin n

n Bonn

n Neustrelitz

Weilheim n

Bremen n n Trauen

Lampoldshausen n

Stuttgart n

Stade n

Augsburg n

n Hamburg

Juelich n

DLR – German Aerospace Research

7700 employees across 32

institutes and facilities at 16

sites

Offices in Brussels, Paris, Tokyo

and Washington


Common methods and expertise

Estimation theory

Signal processing

Signal propagation

Measurement tools

Applications

Mass market

Professional (aviation)

Safety of Life

Space

Air-Ground Communication

Air-to-Air Communication

Surveillance

APNT

LTE Based Positioning

Swarm Navigation

End-to-End Bayesian Navigation

Signal Propagation

Maritime Communications

Car-to-X Communications

Train-to-X Communications

Railway Collision Avoidance

Relative Positioning

Pedestrian & Vehicular Navigation

40 employees: 19 PhD students, 17 PhD scientists,

2 technicians, 2 secretaries

Institute of Communications and Navigation

Department Communications Systems

Organisation of the Department

Decentralised autonomous methods

Obstacle avoidance

Field tests with flying platforms

Master Thesis‘ Topics

o Two-way Ranging with LDACS1.

o An ultrasonic sensor array for environment sounding with sparsity

constraints.

o Attribute-distributed learning for multi-agent robotic swarms.

o Consensus Algorithms for Optimal Multi-Agent Path Planning in the

Presence of Uncertainty.

o Multipath Assisted Positioning: Mapping of Virtual Transmitters.

o FootSLAM with Multiple Sensors.

o FeetSLAM Automation with and without Wireless Measurements.

o From FootSLAM to MotionSLAM – Non-Walking Motion Modes.


- LDACS: L-band Digital Aeronautical Communications System

Future data link for civil aviation based on OFDM technology

- Besides communication,

LDACS provides ranging functionality

Aircraft just listens to ground stations (GSs);

ranging works like GPS using LDACS GSs as

pseudolites (“satellites on ground”)

- Two-way ranging

Aircraft actively transmits LDACS signal; GS responds

after a pre-determined delay and range is calculated

from signal run-time; mimics DME1 functionality

- Main goals

- Determine accuracy achievable with

two-way ranging

- Develop algorithms to improve accuracy

Two-way Ranging with LDACS

1DME = Distance Measuring Equipment

> Michael Schnell • [email protected] > 23 January 2015 www.DLR.de • Chart 8

- We consider an attribute-distributed learning of L agents in a robotic swarm

Goal: given N instances of the observed attributes 𝑋 and targets Y,

how to learn a nonlinear function 𝑌 = 𝑓(𝑋) in a distributed fashion?

Attribute-distributed learning for multi-agent

robotic swarms

Agent 1

Agent 2

Agent L

> Dmitriy Shutin• [email protected] > 23 January 2015 www.DLR.de • Chart 9

An ultrasonic sensor array for environment

sounding with sparsity constraints

www.DLR.de • Chart 10 > Christoph Manß • [email protected] > 23 January 2015

• Objects can be considered

as „peaks“ in the

environment (sparsity)

• Use compressive sensing

techniques to determine

the location of each object

• Different soundings give

more information of the

environment

• Test the whole array on a

quad

Consensus Algorithms for Optimal Multi-Agent

Path Planning in the Presence of Uncertainty

www.DLR.de • Chart 11 > Alberto Viseras Ruiz • [email protected] > 23 January 2015

o The agent 1 wants to go from A1

to B1.

o We have uncertainty about the

pose, motion and obstacles.

o How can we find the optimal

path while keeping the collision

probability bounded?

A1

1

B1

Chance Constrained

LQR-RRT*




o The agent 1 wants to go from A1

to B1 and agent 2 from A2 to B2.

A1

1 2

A2

B2

B1

Crash!!!

But they can talk

with each other…




o They can talk and agree that

agent 1 will change its route.

o But they have to reach a

consensus.

A1

1 2

A2

B2

B1

o How can we find the global

optimal path so that we keep the

collision probability with obstacles

and agents bounded?

That would be your

work

Position estimation not

possible because

possible position lies on

all positions on the circle

Signal is additionally

reflected on the wall

Multipath Assisted Positioning: Mapping of Virtual Transmitters

- Each multipath components is treated as

signals emitted from virtual transmitters

- Multipath propagation increases the number

of transmitters by virtual transmitters

Problem: - Location of the virtual transmitters

are unknown

- No information about floor-plan

Solution: - Simultaneously estimation of the virtual

transmitter and receiver position

Master Thesis: - Position of virtual transmitters are static over

time

- Derive a mapping algorithm for virtual

transmitters.

Virtual transmitter: Mirroring the

transmitter on the wall

Map with one real transmitter and many virtual

transmitters!

Using multipath components for positioning allows

positioning with only one physical transmitter!

> Christian Gentner • [email protected] > 23 January 2015 www.DLR.de • Chart 14

FootSLAM with Multiple Sensors

FootSLAM estimates an indoor map with an IMU placed on the foot assuming

walking and making use of the rest phase of the foot to reduce the drift

(ZUPT).

Master Thesis:

Extend FootSLAM framework:

• Several sensors on foot and on body

• Combine measurements in appropriate way

• Performance evaluation with multiple sensors

• Investigate robustness against sensor failures

Estimated

FootSLAM

map:

IMU placed on

the foot

> Susanna Kaiser • [email protected] > 23 January 2015 www.DLR.de • Chart 15

FeetSLAM Automation with and without Wireless

Measurements

Collaborative Mapping: Combined

FeetSLAM map from these six data sets:

FootSLAM estimates an indoor map. FeetSLAM combines several maps:

Challenges:

Master Thesis:

• FootSLAM maps rotational invariant map orientation unknown

• Starting point usally also unknown

• Map fusion only successful, if position and orientation of maps given

Enhance the alignment and combination of the maps in FeetSLAM by

• automating map alignment with and without available (wireless) prior information

• investigating suitable, available wireless prior information for FeetSLAM,

e.g., UWB, GPS when starting outdoors, UMTS, or, WLAN, and the performance thereof


From FootSLAM to MotionSLAM – Non-Walking

Motion Modes

Challenges:

Master Thesis:

New motion modes, e.g., crawling, kicking stairs, or fast running

lead to measurements where foot rest assumption may not be valid

Extend FootSLAM framework:

• Enable at least crawling

• Combine two sensors: foot-mounted and hip- or thigh-mounted to estimate

motion mode

FootSLAM estimates an indoor map with an IMU placed on the foot assuming

walking and making use of the rest phase of the foot to reduce the drift

(ZUPT).

Estimated

FootSLAM

map:

IMU placed on

the foot and at

hip

“Standing”


- You have good to excellent marks!

- You are creative and you want to put your acquired knowledge into practice!

- You enjoy working with a young, dynamic, international team of researchers!

- You are interested in the multi-faceted field of aerospace, energy and

transport!

- Flexible starting dates depending on individual topic/supervisor

Apply for the exchange program with the German Aerospace Center

Until 09/02/2015

Application: List of topics according to your preferences, CV, Motivation letter,

Transcript of records, Average Grade, Some restrictions about the starting date.

(in English)

Phone interview with responsible persons of Master‘s thesis in DLR

How to apply? → contact your university‘s coordinator

Department Communications Systems

Career Opportunities

> Alberto Viseras Ruiz • Presentation DLR > 23 January 2015 www.DLR.de • Chart 18

DLR exchange program

• Duties:

- Daily presence at DLR at core office times

- Submission of a preliminary (but corrected) version of the thesis after 6 months

- Cooperation with supervisors at DLR and your university

• Provided:

- Computer (portable if required), sensors, working material

- Supervision and career prospects

- German lessons

• Financial Terms:

- In total >= 800 EUR/month

- Room costs: about 400 EUR/month


DLR exchange program

- Timeframe:

Research Period:

• At DLR IKN near Munich

• Contract for 6 months

• Mid-term presentation after 3 months

• Final presentation at DLR at the end

of the period

• Regular reports to university’s

supervisor.

• Writing up the final thesis

• Objective is a scientific publication

Pre-Working period:

• Sending of official DLR

application documents

• Application for ERASMUS

programme for practical

trainings

• Thereby acceptance of DLR-

University-exchange rules

• Familiarization guided by

university and DLR tutors

Fine-Tuning:

• Improving

thesis

• Working on

publication

• Submission

in your

university

6 months of Master‘s thesis at DLR



Email: [email protected]

Apply until 09.02 !

Documents

German Aerospace Center (DLR) - UPM · Railway Collision Avoidance Relative Positioning Pedestrian & Vehicular Navigation 40 employees: 19 PhD students, 17 PhD scientists, 2 technicians,