Summer Term 2016


Autonomous Robot Navigation Seminar

Tutor: Eduardo Ferrera

Nowadays, mobile robots are used in many applications, such as rescue missions, surveillance or people assistance. In these applications, robots usually need to operate in unknown environments, so they need to obtain information with their sensors and take intelligent decisions. In general, they proceed in a loop with several steps:

  1. Information is obtained with the sensors on board the robot.
  2. Given the current information the best decision is made.
  3. The decision is carried out by the robot autonomously.

Mainly, mobile robots need to know where they are located and how to navigate safely to other places. For that, they have to use external sensors (e.g., GPS, compass, laser, etc.), plan trajectories, avoid obstacles, etc.

The objectives of this seminar are to learn about different robotic issues and learn how to present this scientific knowledge. In particular, the following issues will be covered by this seminar:

  • Obstacle avoidance.
  • Path planning.
  • Indoor localization.
  • Outdoor localization.
  • Map building.
  • Collision avoidance for UAVs.
  • Visual-based navigation.
  • Formation control for UAVs.

This seminar is suitable for bachelor and master students and it will be taught in English. It cannot be chosen by master AI-SE students. Once every two weeks the students need to select one of the proposed topics and perform a short research in the field, write a report and prepare an oral presentation to demonstrate the acquired knowledge. If you want to participate in this seminar or for further information, please contact Eduardo Ferrera (eduardo.ferrera@uni-due.de).

The kickoff meeting for this seminar will take place in Room S-A 126, from 14:00h to 16:00h, on Thursday, April 14th, 2016. It is mandatory to attend this meeting in order to participate in the seminar.

Entry in LSF: Seminar

Case Study: Location-based Services

Lecturer: Dr. Marcus Handte
This case study covers fundamental concepts related to the development of location-based services from a theoretical and practical perspective. During the first half of the semester, basic models, algorithms, data structures and applications are introduced in a series of lectures with associated programming exercises. During the second half of the semester, participants will be designing and prototyping a location-based service for mobile (Android) devices on top of an existing infrastructure for indoor localization.

The theoretical part of the case study covers the following contents:

  • Geometric, symbolic and hybrid location models
  • Localization systems and algorithms for outdoor and indoor environments
  • (Energy-)efficient location acquisition and communication
  • Server-based and server-less location data management
  • Security and privacy aspects related to location information
  • Example location-based services and applications

The case study (4SWS) is suitable for participants at the Master level. Grading is based on the practical programming work during the semester and an oral exam at the end of the semester.  Depending on the participants, the course can be held either in English or in German. The lecture part of the course will take place Thursdays from 9.00h to 11.00h in SA-126. The kickoff takes place on Thursday, April 14th in SA-126. Participation during the kickoff meeting is mandatory. To access the materials (slides, papers, etc.) of the course and to get important notifications, please subscribe to the Moodle page of the course. The password will be published here soon.

Entry in LSF: Case-Study

Context Recognition Seminar

Tutor: Marcus Handte 

Nowadays, most devices are equipped with differnt types of networking technology and a broad spectrum of sensors. Examples include gyroscopes, accelerometers, cameras, and microphones. To provide better task support, future applications will have to use the sensors of multiple devices to determine the state of their environment in an automated fashion. This requires novel software systems and signal processing algorithms to derive high-level context information from low-level sensor readings.

The seminar topics will cover a selection of systems and algorithms to recognize different types of context. Furthermore, they cover supportive architectures and protocols to recognize context in a distributed manner. Thereby, the seminar focuses on light-weight approaches that can be implemented on resource-poor devices. Participants will be able to select their topic of choice from the set of available topics.

Participants will have to do a literature research and they will have to create a high quality written report. Furthermore, they will have to give an oral presentation of their topics.

This seminar is suitable for students at the bachelor and master/diploma level. However, it cannot be chosen by master AI-SE students. Furthermore, depending on the number and type of participants, this seminar might be given in English and German. Please also note that the maximum number of participants is limited. If you have questions regarding the seminar, please send an email to marcus.handte@uni-due.de.

The kickoff meeting for this seminar will take place on Thursday, 14.04.2016 between 16.00h and 17.30h in SA 126. Participation in this meeting is mandatory.

Entry in LSF: Bachelor and Master.

Master Project: Augmented Reality Navigation

Tutor: Marcus Handte 

With their broad variety of sensors and their ability to render 3D models in real time, modern smart phones are an interesting platform to support augmented reality visualizations. In order to overlay a virtual 3D world on top of camera images of the physical world, it is necessary to properly capture the user’s orientation using the sensors built into the device and to adjust the model accordingly.

In this project, the participants will develop a navigation application for Android devices that leverages OpenStreetMap data to route the user to a configurable destination. In addition to the widely used map-based visualization, the application will include an augmented reality visualization that overlays the remaining route on top of a video generated by the device’s camera. While creating the application, participants will have to work with the sensor framework provided by Android and they will have to learn the basics of Open GL.

This course may be held in German and English depending on the number and type of participants. The project is suitable for students at the master level. If you want to participate in the project, please send an email to marcus.handte@uni-due.de.

Operating Systems Design and Implementation

Lecturer and exercises: Prof. Rasit Eskicioglu (University Manitoba, Canada)

This is a senior level course that provides an in-depth examination of design and implementation of today`s operating systems. The course is organized in three parts: lectures, labs and readings. The first part of the lectures will introduce a simple, but functional operating system, called xv6 (x86 version 6), which is a re-implementation (at MIT) of Unix Version 6, which was developed in the 1970`s. We will regularly use the computers to study the source code of xv6, as well as developing our own operating system, called JOS.

– Overview of operating systems (review of the first course on OS)
– Internals of xv6 operating System
– This follows the design and implementation of another operating system from scratch (we provide a
skeleton with lowest level components)
– Advance topics (4 weeks)
– This includes reviewing advanced topics through reading several research papers on operating systems

This course is suitable for master students (AI-SE and ISE-CE) and it will be taught in English. For further information, please contact Sascha Jungen (sascha.jungen@uni-due.de).

The kickoff meeting for this lecture with exercises will take place on Monday, April 18th between 10.00h and 11.30h in room S-A 126. It is mandatory to attend this kick-off meeting in order to participate.

This course will be held as a block course over 6 weeks (with 4 hours/week lecture and 4 hours/week exercises) and an oral examination at the end (between 13th and 17th June).

Lecture weekly: Monday 10 a.m. to 12 p.m. and Wednesday 4 p.m. to 6 p.m. in Room S-A 215
Excercises weekly: Monday 12 p.m. to 2 p.m. and Wednesday 2 p.m. to 4 p.m. in Room S-A 215

More information can be found on our Moodle2 page. The password will be announced in the Kickoff Meeting.

Entry in LSF: Lecture and exercise 

Sensor Networks

Lecturer: Prof. Dr. Pedro José Marrón, Exercises: Songwei Fu
This lecture describes the fundamental concepts of sensor networks and how they differ from traditional networked systems that do not take energy and resource constraints into account. During the experiments, the students will deal with real-world deployments of sensor networks and use real sensor nodes to understand better the effects of real-world phenomena in aspects like link quality, localization, etc.

Place and Time:

  • Place:  S-A 126 (Lecture), S-A 126 (Exercises)
  • Lecture: weekly Wednesday 10:00-12:15 s.t.
  • Exercises: biweekly Thursday  16:00- 18:00 s.t.

The first lecture is held on April 12th 2016; the first exercises on April 14th.

Entry in LSF: Lecture und Exercise

More information can be found on our Moodle2 page. The password will be announced in the first lecture and in the exercises.

Wireless Sensor Network Application Development Project

Tutor: Dr. Matteo Ceriotti
Wireless Sensor Networks (WSNs) have been widely deployed in many application domains including environmental monitoring, surveillance, healthcare, automation control and more. A typical WSN consists of a set of low-powered and inexpensive embedded sensor devices with specific sensing modalities and with computation as well as communication capabilities. These devices collaborate with each other by exchanging data through energy-efficient, short-range radios. The application provides its services by manipulating the sensory data collected by the deployed WSN.

In this project, you will learn how to develop an integrated application providing services by making use of a WSN. The topics that will be covered include:

  • Wireless sensor system programming
  • Sensory data collection
  • Data delivery and communication through IEEE 802.15.4 networks
  • Interfacing between the user and the deployed WSN

This course will be taught in English. If you are not sure whether you fulfill the requirements or if you want to participate in the project, please send an email to matteo.ceriotti@uni-due.de.

The kickoff meeting for this project will take place on Friday, 15.04.2016 between 10.30h and 12.00h in Room S-A 126. This date is still tentative, please check this information for updates or send an email to matteo.ceriotti@uni-due.de to be notified about changes. Participation in this meeting is mandatory.

Entry in LSF: Bachelor and Master.

Moodle page

Wireless Sensor Network Seminar

Tutor: Dr. Chia-Yen Shih
This seminar aims to familiarize student with important research topics in Wireless Sensor Networks. The covered topics include: routing, localization, sensing coverage and communication connectivity, multi-channel communication, sensor networks simulation, modeling techniques on radio models, mobility models and sensing modalities, camera sensor networks.

This seminar is offered as a bachelor and a master seminar. It cannot be chosen by master AI-SE students. The student needs to select one of above topics and to perform in-depth research study on the chosen topic. By the end of the semester, the student is required to turn in a well-written report and to prepare an oral presentation to demonstrate the result of the study.

For further information about the seminar, please contact Dr. Chia-Yen Shih at chia-yen.shih@uni-due.de.

The first meeting for the seminar will take place in Room SA126 at 13:30-15:00 on Tuesday, 12.04.2016. It is mandatory to attend the first meeting in order to participate the seminar.

Entry in LSF: Seminar