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List of projects

Very low radiated power UWB communication

Contact: Prof. Jean-Yves Le Boudec             Relevant publications

Last updated on: Sept. 05

This project investigates very low radiated power ultra-wide band (UWB) communications. In particular, we are interested by the implications that low radiated power has on the design of the MAC and physical layer.

For more information, please consult http://icawww1.epfl.ch/uwb/mics.

Deployment of sensor networks

Contact: Prof. Friedemann Mattern , Jan Beutel             Relevant publications

Last updated on: July 07

This project addresses the deployment and programming problem of large-scale sensor networks in real-word settings. Its ultimate goal is to replace the current "trial-and-error deployment practice" with a systematic approach.

Applications

To allow the deployment of a wide range of sensor network applications.

The project assets

The project follows three different, but related research avenues: firstly, it explores the opportunities of so-called deployment support networks . These are separate wireless networks installed alongside the actual sensor network in order to observe, examine and control it.

Secondly, emphasis is put on distributed sensor network debuggers . They make use of deployment support networks to test and debug a target sensor network in real-world settings.

Finally, the project looks at global programming models . The goal is to achieve application development by programming whole sensor networks rather than individual nodes, and by focusing on application level concepts rather than system level concepts.

What has been achieved so far?

While a number of simulation tools and wired testbeds are currently in use, they cannot capture well many real-world influences for networks of realistic size. Also, good concepts for systematic testing and management of sensor networks are largely missing. The lack of appropriate tools and methods and their need in practice motivates the research goals of the project.

Where does the project stand now?

An initial version of the Deployment Support Network (DSN) has been released to the public. The DSN serves as a foundation for the Sensor Network Inspection Framework (SNIF), a prototype of a sensor network debugger that can identify and localize typical problems encountered during the deployment of sensor networks. Also building upon DSN, a distributed test methodology has been proposed to check the compliance of a sensor network implementation with the specification.

Finally, different approaches for global programming models have been considered. One such approach called "generic role assignment" supports the automatic assignment of roles to sensor nodes.

Modular and composable platform for sensor and actuator networks

Contact: Prof. Thomas Henzinger             Relevant publications

Last updated on: July 07

Platforms The aim of this research project is to develop methodologies for the design of composable platforms of embedded and resource constrained distributed systems such as wireless sensor and actuator networks.

Applications

It is intended to use the methods and concepts developed in this project for applications studied by the center.

The project assets

A method will be developed for local and global composable analysis of essential functional and resource properties of embedded software and hardware components, such as energy, buffer space, and timing properties.

What has been achieved so far?

We have developed composable distributed code generation techniques for time triggered languages, software verification algorithms, and the mathematics based on game theory for the composition of time and resource constraining component interfaces.

Where does the project stand now?

We continue to develop a mathematical theory and software platform for the composition of embedded components.

Distributed odor source localization using a miniature multi-robot system

Contact: Prof. Alcherio Martinoli , Thomas Lochmatter             Relevant publications

Last updated on: June 08

This project aims at exploring robotic systems to localize sources that release airborne molecules or particles. In particular, our main objective is to find out how and in which circumstances multi-robot systems are preferred over single robots. The research focus of the project is on the design and analysis of distributed, intelligent algorithms for coordinating multiple robots engaged in distributed odor localization.

Applications:

Mobile robots equipped with appropriate chemical sensors could replace dogs and rats in many applications.  Humanitarian demining or search and rescue operations are among the potential future applications of such technology. Moreover, odor sniffing mobile robots could also be used to enhance security on airports or country borders, to detect pipe leaks in industrial plants, or to track offensive smells in the environment.

Whereas training dogs is lengthy and expensive, programming and calibrating robots is far easier. Robots can be built in masses within short time, are immediately available after production, and can operate in a massive parallel system. In addition, mobile robots can be used regardless of their mood or sleepiness. (Dogs need a rest after a couple of hours.) Hence, mobile robots would be a relatively cheap alternative to dogs.

The project assets:

The main focus of this project is the exploration and comparison of distributed, intelligent algorithms for odor source localization. Key differences to their single-robot counterparts are highlighted and quantified in experiments with real robots and in simulation. Important metrics are robustness and speed in the mission accomplishment. The considered algorithms go beyond bio-inspired solutions. They leverage, for instance, direct RF communication between the robots and algorithms based on information theory concepts.

The experiments with real robots are carried out in a wind tunnel at EPFL, and hence in an controlled environment with reproducible fluid dynamic conditions. To our knowledge, this is the first project that studies multi-robot odor source localization algorithms with real robots in a controlled environment.

What has been achieved so far?

Professor Alcherio Martinoli, while working at the California Institute of Technology (Caltech), has participated for about one and a half years in the DARPA-ONR Chemical Plume Tracing Program. This effort has resulted in a series of publications culminating in two journal papers [Hayes02, Hayes03]. In addition to being able to detect the plume it its distal zone rather than only in its proximity as most of the previous robotic efforts did, Prof. Martinoli’s group demonstrated for the first time that distributed source localization was feasible and increased the performance of a single robot depending on the search scenario.

At EPFL, a new, smaller and more powerful robotic platform than that used at Caltech, the Khepera III, has been developed by K-Team SA in collaboration with DISAL. The Khepera III robot has been equipped with a VOC sensor connected to a pump, and a sensory module based on an array of hotwires able to measure wind strength and direction.  This prototype was successfully used to compare three single-robot algorithms with various parameters in a laminar flow. The experiments showed that casting – a bio-inspired algorithm that has been frequently used so far – is clearly worse than algorithms based on upwind surge (surge-spiral and surge-cast). Numerical simulations and theoretical considerations confirmed these findings.

In addition, some exploration has been done with multi-robot algorithms in simulation, plume tracking with bio-inspired algorithms in environments with obstacles (simulation and real-robot experiments), and information theoretic approaches (simulation and real-robot experiments).

Where does the project stand now?

The wind tunnel set-up has been customized for systematically carrying out distributed odor localization experiments. A fleet of 20 Khepera III robots is available for this project. The prototypes of sensory modules for olfaction and anemometry have been developed and currently being optimized. In a few months, the sensor modules for 20 robots will be manufactured, allowing us to run multi-robot experiments in the wind tunnel. Additional efforts in the deployment of a multi-camera system in the wind tunnel as well as refinement of simulation tools are foreseen in the near future.

Real-time avalanche and landslide analysis through sensor networks

Contact: Prof. Edoardo Charbon , Christophe Ancey             Relevant publications

Last updated on: July 07

This project aims at gaining insight into the dynamics of rapid gravity-driven flows, such as avalanches and earth mass movements, by using a sensor-network based monitoring system.

Applications

To improve fluid-mechanics models describing the flow behavior of avalanches. The system can also be used for hazard warning purposes (e.g., for detecting acceleration of a landsliding mass), thus enabling appropriate measures to be taken on time to minimize loss of life or for rescue operations (e.g., to detect skiers buried in an avalanche).

The project assets

The sensor network measures the displacement/velocity field inside a flowing bulk. Before the material is released, the sensor nodes are spread onto the surface or inside the material. After release, the information of each node is monitored to determine the flow structure.

The main tasks are twofold: constructing a sensor network and interpreting the data to build more accurate fluid-dynamics models.

At the core of the monitoring system is a network of sensor nodes. To achieve an accuracy of a few centimetres, ultra- wideband radio links is implemented and novel algorithms are used. For the data interpretation, the project will benefit from a new instrumented platform at EPFL (inclined channel), where the method could be tested against lab avalanches.

What has been achieved so far?

The fluid-dynamics models used so far in predicting mass movements such avalanches rely on speculative equations and very few is known about the internal structure of avalanches. Field measurements only provide insight into shape characteristics (e.g., avalanche speed).

Where does the project stand?

Preliminary experiments are ongoing to simulate mass movements in a well-controlled environment on the lab scale. Prior to testing the sensor efficiency in the field, we must be able to determine the flow structure using independent measurement techniques in the lab. Particle imaging techniques will be used.

 
   
 
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