Multirobot Tethering for Localization and Control

Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. This becomes more critical if the state estimate is an integral part of system control. We investigate the use of particle filter estimation techniques on a hovercraft vehicle. The marginally stable dynamics of a hovercraft require reliable state estimates for proper stability and control. We use the Monte Carlo localization method, which implements a particle filter in a recursive state estimate algorithm. An H-infinity controller, designed to accommodate the latency inherent in our state estimation, provides stability and controllability to the hovercraft. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. By tracking and controlling the secondary robot, we can position the mobile feature throughout the environment to ensure a high confidence estimate, thus maintaining stability in the system. A laser rangefinder is the sensor the hovercraft uses to track the secondary robot, observe the environment, and facilitate successful localization and stability in motion.

Localization of a mobile robot based on odometry and natural landmarks using extended kalman filter

SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

Expression-based and co-localization detection of arabinogalactan protein 6 and arabinogalactan protein 11 interactors in Arabidopsis pollen and pollen tubes

Arabinogalactan proteins (AGPs) are cell wall proteoglycans that have been shown to be important for pollen development. An Arabidopsis double null mutant for two pollen-specific AGPs (agp6 agp11) showed reduced pollen tube growth and compromised response to germination cues in vivo. A microarray experiment was performed on agp6 agp11 pollen tubes to search for genetic interactions in the context of pollen tube growth. A yeast two-hybrid experiment for AGP6 and AGP11 was also designed.

Molecular Characterization and Localization of the NAD(P)H Oxidase Components gp91-phox and p22-phox in Endothelial Cells

The production of reactive oxygen species (ROS) within endothelial cells may have several effects, including alterations in the activity of paracrine factors, gene expression, apoptosis, and cellular injury. Recent studies indicate that a phagocyte-type NAD(P)H oxidase is a major source of endothelial ROS. In contrast to the high-output phagocytic oxidase, the endothelial enzyme has much lower biochemical activity and a different substrate specificity (NADH.NADPH). In the present study, we (1) cloned and characterized the cDNA and predicted amino acid structures of the 2 major subunits of rat coronary microvascular endothelial cell NAD(P)H oxidase, gp91-phox and p22-phox; (2) undertook a detailed comparison with phagocytic NADPH oxidase sequences; and (3) studied the subcellular location of these subunits in endothelial cells. Although these studies revealed an overall high degree of homology (.90%) between the endothelial and phagocytic oxidase subunits, the endothelial gp91-phox sequence has potentially important differences in a putative NADPH-binding domain and in putative glycosylation sites. In addition, the subcellular location of the endothelial gp91-phox and p22-phox subunits is significantly different from that reported for the neutrophil oxidase, in that they are predominantly intracellular and collocated in the vicinity of the endoplasmic reticulum. This first detailed characterization of gp91-phox and p22-phox structure and location in endothelial cells provides new data that may account, in part, for the differences in function between the phagocytic and endothelial NAD(P)H oxidases.

CONCURRENT LOCALIZATION AND MAPPING WITH SONAR SENSORS AND CONSIDERATION OF VEHICLE MOTION

Simultaneous Localization and Mapping (SLAM) is a procedure used to determine the location of a mobile vehicle in an unknown environment, while constructing a map of the unknown environment at the same time. Mobile platforms, which make use of SLAM algorithms, have industrial applications in autonomous maintenance, such as the inspection of flaws and defects in oil pipelines and storage tanks. A typical SLAM consists of four main components, namely, experimental setup (data gathering), vehicle pose estimation, feature extraction, and filtering. Feature extraction is the process of realizing significant features from the unknown environment such as corners, edges, walls, and interior features. In this work, an original feature extraction algorithm specific to distance measurements obtained through SONAR sensor data is presented. This algorithm has been constructed by combining the SONAR Salient Feature Extraction Algorithm and the Triangulation Hough Based Fusion with point-in-polygon detection. The reconstructed maps obtained through simulations and experimental data with the fusion algorithm are compared to the maps obtained with existing feature extraction algorithms. Based on the results obtained, it is suggested that the proposed algorithm can be employed as an option for data obtained from SONAR sensors in environment, where other forms of sensing are not viable. The algorithm fusion for feature extraction requires the vehicle pose estimation as an input, which is obtained from a vehicle pose estimation model. For the vehicle pose estimation, the author uses sensor integration to estimate the pose of the mobile vehicle. Different combinations of these sensors are studied (e.g., encoder, gyroscope, or encoder and gyroscope). The different sensor fusion techniques for the pose estimation are experimentally studied and compared. The vehicle pose estimation model, which produces the least amount of error, is used to generate inputs for the feature extraction algorithm fusion. In the experimental studies, two different environmental configurations are used, one without interior features and another one with two interior features. Numerical and experimental findings are discussed. Finally, the SLAM algorithm is implemented along with the algorithms for feature extraction and vehicle pose estimation. Three different cases are experimentally studied, with the floor of the environment intentionally altered to induce slipping. Results obtained for implementations with and without SLAM are compared and discussed. The present work represents a step towards the realization of autonomous inspection platforms for performing concurrent localization and mapping in harsh environments.

THE ROLE OF THE MECHANICAL ENVIRONMENT ON CANCER CELL TRANSMIGRATION AND MRNA LOCALIZATION

Most cancer-related deaths are due to metastasis formation, the ability of cancer cells to break away from the primary tumor site, transmigrate through the endothelium, and form secondary tumors in distant areas. Many studies have identified links between the mechanical properties of the cellular microenvironment and the behavior of cancer cells. Cells may experience heterogeneous microenvironments of varying stiffness during tumor progression, transmigration, and invasion into the basement membrane. In addition to mechanical factors, the localization of RNAs to lamellipodial regions has been proposed to play an important part in metastasis. This dissertation provides a quantitative evaluation of the biophysical effects on cancer cell transmigration and RNA localization. In the first part of this dissertation, we sought to compare cancer cell and leukocyte transmigration and investigate the impact of matrix stiffness on transmigration process. We found that cancer cell transmigration includes an additional step, ‘incorporation’, into the endothelial cell (EC) monolayer. During this phase, cancer cells physically displace ECs and spread into the monolayer. Furthermore, the effects of subendothelial matrix stiffness and endothelial activation on cancer cell incorporation are cell-specific, a notable difference from the process by which leukocytes transmigrate. Collectively, our results provide mechanistic insights into tumor cell extravasation and demonstrate that incorporation into the endothelium is one of the earliest steps. In the next part of this work, we investigated how matrix stiffness impacts RNA localization and its relevance to cancer metastasis. In migrating cells, the tumor suppressor protein, adenomatous polyposis coli (APC) targets RNAs to cellular protrusions. We observed that increasing stiffness promotes the peripheral localization of these APC-dependent RNAs and that cellular contractility plays a role in regulating this pathway. We next investigated the mechanism underlying the effect of substrate stiffness and cellular contractility. We found that contractility drives localization of RNAs to protrusions through modulation of detyrosinated microtubules, a network of modified microtubules that associate with, and are required for localization of APC-dependent RNAs. These results raise the possibility that as the matrix environment becomes stiffer during tumor progression, it promotes the localization of RNAs and ultimately induces a metastatic phenotype.

Silencing the gip gene of Phytophthora cinnamomi by iRNA and studying the subcellular localization of GIP and NPP1 proteins

Ink Disease is considered one of the most important causes of the decline of chestnut orchards. The break in yield of Castanea sativa Mill is caused by two species: Phytophthora cinnamomi and Phytophthora cambivora, being the first one the foremost pathogen of ink disease in Portugal. P. cinnamomi is one of the most aggressive and widespread plant pathogen with nearly 1,000 host species. This oomycete causes enormous economic losses and it is responsible for the decline of many plant species in Europe and worldwide. Up to now no efficient treatments are available to fight these pathogens. Because of the importance of chestnut at economical and ecological levels, especially in Portugal, it becomes essential to explore the molecular mechanisms that determine the interaction between Phytophthora species and host plants through the study of proteins GIP (glucanase inhibitor protein) and NPP1 (necrosis-inducing Phytophthora protein 1) produced by P. cinnamomi during the infection. The technique of RNA interference was used to knockdown the gip gene of P. cinnamomi. Transformants obtained with the silenced gene have been used to infect C. sativa, in order to determine the effect of gene silencing on the plant phenotype. To know more about the function of GIP and NPP1 involved in the mechanism of infection, the ORF’s of gip and npp1 genes have been cloned to the pTOR-eGFP vector for a future observation of P. cinnamomi transformants with fluorescent microscopy and determination of the subcellular localization. Moreover the prediction by bioinformatics tools indicates that both GIP and NPP1 proteins are secreted. The results allow to predict the secretory destination of both GIP and NPP1 proteins and confirm RNAi as a potential alternative biological tool in the control and management of P. cinnamomi. Keywords:

Alzheimer’s electroencephalogram event scalp and source localization

Alzheimer’s disease is the most common cause of dementia which causes a progressive and irreversible impairment of several cognitive functions. The aging population has been increasing significantly in recent decades and this disease affects mainly the elderly. Its diagnostic accuracy is relatively low and there is not a biomarker able to detect AD without invasive tests. Despite the progress in better understanding the disease there remains no prospect of cure at least in the near future. The electroencephalogram (EEG) test is a widely available technology in clinical settings. It may help diagnosis of brain disorders, once it can be used in patients who have cognitive impairment involving a general decrease in overall brain function or in patients with a located deficit. This study is a new approach to improve the scalp localization and the detection of brain anomalies (EEG temporal events) sources associated with AD by using the EEG.

Molecular identification and localization of filamentous symbiotic bacteria associated with the hydrothermal vent annelid Alvinella pompejana

Alvinella pompejana is a polychaetous annelid that inhabits high temperature environments associated with active deep-sea hydrothermal vents along the East Pacific Rise. A unique and diverse epibiotic microflora with a prominent filamentous morphotype is found associated with the worm's dorsal integument. A previous study established the taxonomic positions of two epsilon proteobacterial phylotypes, 13B and 5A, which dominated a clone library of 16S rRNA genes amplified by PCR from the epibiotic microbial community of an A. pompejana specimen. In the present study deoxyoligonucleotide PCR primers specific for phylotypes 13B and 5A were used to demonstrate that these phylotypes are regular features of the bacterial community associated with A. pompejana. Assaying of other surfaces around colonies of A. pompejana revealed that phylotypes 13B and 5A are not restricted to A. pompejana. Phylotype 13B occurs on the exterior surfaces of other invertebrate genera and rock surfaces, and phylotype 5A occurs on a congener, Alvinella caudata. The 13B and 5A phylotypes were identified and localized on A. pompejana by in situ hybridization, demonstrating that these two phylotypes are, in fact, the prominent filamentous bacteria on the dorsal integument of A. pompejana. These findings indicate that the filamentous bacterial symbionts of A. pompejana are epsilon Proteobacteria which do not have an obligate requirement for A. pompejana.

Purification, biochemical characterization and localization at single cell resolution of Matrix Gla Protein (MGP) and Bone Gla Protein (BGP) in the teleost fish Argyrosomus regius

Tese de dout. em Química, Faculdade de Ciências do Mar e do Ambiente, Univ. do Algarve, 2002

Enhancement of non-viral transfection efficiency with nuclear localization signal peptides

Dissertação de Mestrado, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016

ViDRILO: The Visual and Depth Robot Indoor Localization with Objects information dataset

In this article we describe a semantic localization dataset for indoor environments named ViDRILO. The dataset provides five sequences of frames acquired with a mobile robot in two similar office buildings under different lighting conditions. Each frame consists of a point cloud representation of the scene and a perspective image. The frames in the dataset are annotated with the semantic category of the scene, but also with the presence or absence of a list of predefined objects appearing in the scene. In addition to the frames and annotations, the dataset is distributed with a set of tools for its use in both place classification and object recognition tasks. The large number of labeled frames in conjunction with the annotation scheme make this dataset different from existing ones. The ViDRILO dataset is released for use as a benchmark for different problems such as multimodal place classification and object recognition, 3D reconstruction or point cloud data compression.

A hybrid localization approach in 3D wireless sensor network

Location information acquisition is crucial for many wireless sensor network (WSN) applications. While existing localization approaches mainly focus on 2D plane, the emerging 3D localization brings WSNs closer to reality with much enhanced accuracy. Two types of 3D localization algorithms are mainly used in localization application: the range-based localization and the range-free localization. The range-based localization algorithm has strict requirements on hardware and therefore is costly to implement in practice. The range-free localization algorithm reduces the hardware cost but at the expense of low localization accuracy. On addressing the shortage of both algorithms, in this paper, we develop a novel hybrid localization scheme, which utilizes the range-based attribute RSSI and the range-free attribute hopsize, to achieve accurate yet low-cost 3D localization. As anchor node deployment strategy plays an important role in improving the localization accuracy, an anchor node configuration scheme is also developed in this work by utilizing the MIS (maximal independent set) of a network. With proper anchor node configuration and propagation model selection, using simulations, we show that our proposed algorithm improves the localization accuracy by 38.9% compared with 3D DV-HOP and 52.7% compared with 3D centroid.

RSSI-based localization of a wireless sensor node with a flying robot

We consider the problem of navigating a ying robot to a specific sensor node within a wireless sensor network. This target sensor node periodically sends out beacons. The robot is capable of sensing the received signal strength of each received beacon (RSSI measurements). Existing approaches for solving the sensor spotting problem with RSSI measurements do not deal with noisy channel conditions and/or heavily depend on additional hardware capabilities. In this work we reduce RSSI uctuations due to noise by continuously sampling RSSI values and maintaining an exponential moving average (EMA). The EMA values enable us to detect significant decrease of the received signal strength. In this case it is reasoned that the robot is moving away from the sensor. We present two basic variants to decide a new moving direction when the robot moves away from the sensor. Our simulations show that our approaches outperform competing algorithms in terms of success rate and ight time. Infield experiments with real hardware, a ying robocopter successfully and quickly landed near a sensor placed in an outdoor test environment. Traces show robustness to additional environmental factors not accounted for in our simulations.