Probabilistic Path Discovery with Snakes in Ad Hoc Networks

Many routing protocols for wireless ad hoc networks proposed in the literature use flooding to discover paths between the source and the destination node. Despite various broadcast optimization techniques, flooding remains expensive in terms of bandwidth and energy consumption. In general, O(N) nodes are involved to discover a path. In this thesis, we prove through a theoretical model that probabilistic path discovery is possible by involving O(sqrt(N)) nodes only. The constant factor depends on the desired path discovery probability. Using a novel network primitive that we call snakes, we introduce practical and cheap probabilistic path discovery algorithms. These algorithms rely on the same network model and assumptions as its flooding counterparts, i. e., that the network is unstructured and that nodes only know their immediate (one-hop) neighbors. Numerical simulations in a static network show that these algorithms achieve path discovery probabilities close to the theoretical optimum. We further present a snake-based algorithm for mobile ad hoc networks and several techniques to enhance the performance in some specific networks

Base Stations in Mobile Ad-Hoc Networks

Multi-hop ad-hoc networks consist of nodes which cooperate by forwarding packets for each other to allow communication beyond the power range of each node. In pure ad-hoc networks, no additional infrastructure is required to allow the nodes to communicate. Multi-hop hybrid networks are a combination of ad-hoc and cellular networks. As in ad-hoc networks, the nodes forward packets on behalf of other nodes. However, a few base stations are introduced. This enables long-range communication, increases connectivity and allows centralized services. In our work, we investigate the problem of placing base stations in multi-hop hybrid networks. Since nodes extend the service area by themselves, conventional cellular approaches are not suitable for such networks. We propose the Cluster Covering Algorithm, an algorithm which takes into account the percolation phenomenon, and compare it with several greedy algorithms. We measure the connectivity through different simulations on real population distribution data of Zurich (CH), the Surselva Valley (CH) and Finland. The simulation results show that the Cluster Covering Algorithm outperforms the greedy algorithms

Tracking an Odor Plume in a Laminar Wind Field with the Crosswind-Surge Algorithm

We introduce a novel bio-inspired odor source localization algorithm (surge-cast) for environments with a main wind flow and compare it to two well- known algorithms. With all three algorithms, systematic experiments with real robots are carried out in a wind tunnel under laminar flow conditions. The algo- rithms are compared in terms of distance overhead when tracking the plume up to the source, but a variety of other experimentally measured results are provided as well. We conclude that the surge-cast algorithm yields significantly better performance than the casting algorithm, and slightly better performance than the surge-spiral algorithm

Simulation Experiments with Bio-Inspired Algorithms for Odor Source Localization in Laminar Wind Flow

We compare three bio-inspired odor source localization algorithm (casting, surge-spiral and surge-cast) for environments with a main wind flow in simulation. The wind flow is laminar and the simulation setup similar to the setup in the wind tunnel in which we have carried out similar experiments with real robots. The algorithms are compared in terms of success rate and distance overhead when tracking the plume up to the source. We conclude that the algorithms based on upwind surge yield significantly better performance than pure casting

Geruchslokalisation mit mobilen Robotern

Hunde werden aufgrund ihrer exzellenten Nase oft zur Suche von Minen, Bomben, Drogen oder verschütteten Menschen eingesetzt. Mit elektronischen Geruchssensoren könnten für solche Anwendungen bald auch mobile Roboter zum Einsatz kommen. Neben guten Geruchssensoren und passenden Robotern sind aber auch entsprechende Suchalgorithmen notwendig - und die komplexe Ausbreitung von Rauch und Duftmolekülen in der Luft macht die Suche nach Geruchsquellen zu einer grossen Herausforderung

Odor Source Localization with Mobile Robots

Because of their excellent olfactory sense, dogs are often used to find bombs, mines, drugs, or people buried by avalanches. For such applications, autonomous mobile robots could be used in the future. Electronic sensors already exist for a wide variety of substances, and are still being actively researched. Mobile robots are an important area of research, too. But beyond a good sensor and a suitable robotic platform, a third component is required: odor source localization algorithms – and due to the complex propagation of odor molecules in the air, tracking down odor sources is still a big challenge

SwisTrack - A Flexible Open Source Tracking Software for Multi-Agent Systems

Vision-based tracking is used in nearly all robotic laboratories for monitoring and extracting of agent positions, orientations, and trajectories. However, there is currently no accepted standard software solution available, so many research groups resort to developing and using their own custom software. In this paper, we present Version 4 of SwisTrack, an open source project for simultaneous tracking of multiple agents. While its broad range of pre- implemented algorithmic components allows it to be used in a variety of experimental applications, its novelty stands in its highly modular architecture. Advanced users can therefore also implement additional customized modules which extend the functionality of the existing components within the provided interface. This paper introduces SwisTrack and shows experiments with both marked and marker-less agents

Expression profiling in transgenic FVB/N embryonic stem cells overexpressing STAT3

BACKGROUND: The transcription factor STAT3 is a downstream target of the LIF signalling cascade. LIF signalling or activation is sufficient to maintain embryonic stem (ES) cells in an undifferentiated and pluripotent state. To further investigate the importance of STAT3 in the establishment of ES cells we have in a first step derived stable pluripotent embryonic stem cells from transgenic FVB mice expressing a conditional tamoxifen dependent STAT3-MER fusion protein. In a second step, STAT3-MER overexpressing cells were used to identify STAT3 pathway-related genes by expression profiling in order to identify new key-players involved in maintenance of pluripotency in ES cells. RESULTS: Transgenic STAT3-MER blastocysts yielded pluripotent germline-competent ES cells at a high frequency in the absence of LIF when established in tamoxifen-containing medium. Expression profiling of tamoxifen-induced transgenic FVB ES cell lines revealed a set of 26 genes that were markedly up- or down-regulated when compared with wild type cells. The expression of four of the up-regulated genes (Hexokinase II, Lefty2, Pramel7, PP1rs15B) was shown to be restricted to the inner cell mass (ICM) of the blastocysts. These differentially expressed genes represent potential candidates for the maintenance of pluripotency of ES cells. We finally overexpressed two candidate genes, Pem/Rhox5 and Pramel7, in ES cells and demonstrated that their overexpression is sufficient for the maintenance of expression of ES cell markers as well as of the typical morphology of pluripotent ES cells in absence of LIF. CONCLUSION: Overexpression of STAT3-MER in the inner cell mass of blastocyst facilitates the establishment of ES cells and induces the upregulation of potential candidate genes involved in the maintenance of pluripotency. Two of them, Pem/Rhox5 and Pramel7, when overexpressed in ES cells are able to maintain the embryonic stem cells in a pluripotent state in a LIF independent manner as STAT3 or Nanog

T-cell recognition of chemicals, protein allergens and drugs: towards the development of in vitro assays

Chemicals can elicit T-cell-mediated diseases such as allergic contact dermatitis and adverse drug reactions. Therefore, testing of chemicals, drugs and protein allergens for hazard identification and risk assessment is essential in regulatory toxicology. The seventh amendment of the EU Cosmetics Directive now prohibits the testing of cosmetic ingredients in mice, guinea pigs and other animal species to assess their sensitizing potential. In addition, the EU Chemicals Directive REACh requires the retesting of more than 30,000 chemicals for different toxicological endpoints, including sensitization, requiring vast numbers of animals. Therefore, alternative methods are urgently needed to eventually replace animal testing. Here, we summarize the outcome of an expert meeting in Rome on 7 November 2009 on the development of T-cell-based in vitro assays as tools in immunotoxicology to identify hazardous chemicals and drugs. In addition, we provide an overview of the development of the field over the last two decades

Bio-inspired and probabilistic algorithms for distributed odor source localization using mobile robots

We compare six different algorithms for localizing odor sources with mobile robots. Three algorithms are bio-inspired and mimic the behavior of insects when exposed to airborne pheromones. Two algorithms are based on probability and information theory, and infer the source location by probabilistically merging concentration measurements at different positions in the environment. The last algorithm is a multi-robot algorithm based on a crosswind line formation. The algorithms are mainly compared with respect to their distance overhead – a metric directly related to the speed of an algorithm – and their success rate. The thesis also reports on the influence of various environmental and algorithmic parameters, and compares the algorithms' requirements regarding sensors, self-localization, maps, and other information. Systematic experiments under laminar flow conditions were carried out with real robots in an 18m long wind tunnel. The robots were thereby equipped with an ethanol sensor and a wind direction sensor, and could – if the algorithm required it – access their current position. Overall, more than 500 experimental runs with teams of up to 5 robots were carried out in this wind tunnel. Similar experiments were also carried out in simulation. Over 5000 runs were carried out in a realistically calibrated multi-robot simulator. Odor was thereby simulated as set of filaments that are transported by advection, an approach that generates the intermittence and stochasticity of real plumes. Additional, more than 10000 runs were carried out using body-less simulators under various plume models. Simulation runs were mostly used to quantify the influence of various parameters on the performance of the algorithms. Finally, the thesis also provides theoretical insights into the bio-inspired algorithms, and a general theoretical model for probabilistic odor source localization. For the latter, a number of potential real-world scenarios are discussed on the example of a simplified train station environment. None of the algorithms is strictly superior to all other algorithms. While the probabilistic algorithms offer more flexibility and a slightly better performance, the bio-inspired algorithms are much less CPU and memory intensive, and could therefore be deployed on extremely small and limited robotic platforms. Using multiple robots (with or without collaboration) for odor source localization was found to improve the performance under certain conditions only. The crosswind formation algorithm with 3 robots yielded excellent results, but the multi-robot experiments with the bio-inspired algorithms were hardly better than their single-robot counterparts. The thesis provides reasons for this, and discusses alternatives