A Beacon based Localization System for Autonomous Mobile Robots and its Applications in Traffic and Transport Control

ACCURATE sensing of vehicle position and attitude is still a very challenging problem in many mobile robot applications. The mobile robot vehicle applications must have some means of estimating where they are and in which direction they are heading. Many existing indoor positioning systems are limited in workspace and robustness because they require clear lines-of-sight or do not provide absolute, driftfree measurements.The research work presented in this dissertation provides a new approach to position and attitude sensing system designed specifically to meet the challenges of operation in a realistic, cluttered indoor environment, such as that of an office building, hospital, industrial or warehouse. This is accomplished by an innovative assembly of infrared LED source that restricts the spreading of the light intensity distribution confined to a sheet of light and is encoded with localization and traffic information. This Digital Infrared Sheet of Light Beacon (DISLiB) developed for mobile robot is a high resolution absolute localization system which is simple, fast, accurate and robust, without much of computational burden or significant processing. Most of the available beacon's performance in corridors and narrow passages are not satisfactory, whereas the performance of DISLiB is very encouraging in such situations. This research overcomes most of the inherent limitations of existing systems.The work further examines the odometric localization errors caused by over count readings of an optical encoder based odometric system in a mobile robot due to wheel-slippage and terrain irregularities. A simple and efficient method is investigated and realized using an FPGA for reducing the errors. The detection and correction is based on redundant encoder measurements. The method suggested relies on the fact that the wheel slippage or terrain irregularities cause more count readings from the encoder than what corresponds to the actual distance travelled by the vehicle.The application of encoded Digital Infrared Sheet of Light Beacon (DISLiB) system can be extended to intelligent control of the public transportation system. The system is capable of receiving traffic status input through a GSM (Global System Mobile) modem. The vehicles have infrared receivers and processors capable of decoding the information, and generating the audio and video messages to assist the driver. The thesis further examines the usefulness of the technique to assist the movement of differently-able (blind) persons in indoor or outdoor premises of his residence.The work addressed in this thesis suggests a new way forward in the development of autonomous robotics and guidance systems. However, this work can be easily extended to many other challenging domains, as well.

An Error-Localization, Validation and Optimization Tool for Embedded Code Augmentation: an Architecture Oriented Approach

Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.This dissertation contributes to an architecture oriented code validation, error localization and optimization technique assisting the embedded system designer in software debugging, to make it more effective at early detection of software bugs that are otherwise hard to detect, using the static analysis of machine codes. The focus of this work is to develop methods that automatically localize faults as well as optimize the code and thus improve the debugging process as well as quality of the code.Validation is done with the help of rules of inferences formulated for the target processor. The rules govern the occurrence of illegitimate/out of place instructions and code sequences for executing the computational and integrated peripheral functions. The stipulated rules are encoded in propositional logic formulae and their compliance is tested individually in all possible execution paths of the application programs. An incorrect sequence of machine code pattern is identified using slicing techniques on the control flow graph generated from the machine code.An algorithm to assist the compiler to eliminate the redundant bank switching codes and decide on optimum data allocation to banked memory resulting in minimum number of bank switching codes in embedded system software is proposed. A relation matrix and a state transition diagram formed for the active memory bank state transition corresponding to each bank selection instruction is used for the detection of redundant codes. Instances of code redundancy based on the stipulated rules for the target processor are identified.This validation and optimization tool can be integrated to the system development environment. It is a novel approach independent of compiler/assembler, applicable to a wide range of processors once appropriate rules are formulated. Program states are identified mainly with machine code pattern, which drastically reduces the state space creation contributing to an improved state-of-the-art model checking. Though the technique described is general, the implementation is architecture oriented, and hence the feasibility study is conducted on PIC16F87X microcontrollers. The proposed tool will be very useful in steering novices towards correct use of difficult microcontroller features in developing embedded systems.

Underwater Target Localization, Tracking and Classification

Underwater target localization and tracking attracts tremendous research interest due to various impediments to the estimation task caused by the noisy ocean environment. This thesis envisages the implementation of a prototype automated system for underwater target localization, tracking and classification using passive listening buoy systems and target identification techniques. An autonomous three buoy system has been developed and field trials have been conducted successfully. Inaccuracies in the localization results, due to changes in the environmental parameters, measurement errors and theoretical approximations are refined using the Kalman filter approach. Simulation studies have been conducted for the tracking of targets with different scenarios even under maneuvering situations. This system can as well be used for classifying the unknown targets by extracting the features of the noise emanations from the targets.

The Steady-State and Transient Characteristic Analysis of Thermal Fixing a Photorefractive Hologram Grating in Lithium Niobate

The transient interaction between a refraction index grating and light beams during simultaneous writing and thermal fixing of a photorefractive hologram is investigated. With a diffusion- and photovoltaic-dominated carrier transport mechanism and carrier thermal activation (temperature dependent) considered in Fe:LiNbO3 crystal, from the standpoint of field-material coupling, the theoretical thermal fixing time and the space-charge field buildup, spatial distribution, and temperature dependence are given numerically by combining the band transport model with mobile ions with the coupled-wave equation

Studies on the distribution and abundance of fish eggs and larvae off the south—west coast of India with special reference to scombroids

The broad objective of the present study is to present a synoptic picture of the distribution and abundance of fish eggs and the lmportant groups of fish larvae obtained off the SW coast of India. so as to delineate the spawning areas and seasones of the fish population. with special reference to the scombroid fishes. An attempt was also made to correlate the occurrence of certain categories of larvae and hydrographical factors like temperature and salinity. The present effort was a pioneering one in Indian waters. in as much as it involved systematic and seasonally repetitive collection of ichthyoplankton from a large stretch of our seas and mapping of their distribution and abudance.

“Improved Feature Extraction and Classification Techniques for Multispectral Brain Magnetic Resonance Images”

Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

“Studies on glucose tolerant β-glucosidases from a novel Byssochlamys fulva and their applications in biomass to ethanol conversion”

Beta-glucosidases are critical enzymes in biomass hydrolysis process and is important in creating highly efficient enzyme cocktails for the bio-ethanol industry. Among the two strategies proposed for overcoming the glucose inhibition of commercial cellulases, one is to use heavy dose of BGL in the enzyme blends and the second is to do simultaneous saccharification and fermentation where glucose is converted to alcohol as soon as it is being generated. While the former needs extremely high quantities of enzyme, the latter is inefficient since the conditions for hydrolysis and fermentation are different. This makes the process technically challenging and also in this case, the alcohol generation is lesser, making its recovery difficult. A third option is to use glucose tolerant β-glucosidases which can work at elevated glucose concentrations. However, there are very few reports on such enzymes from microbial sources especially filamentous fungi which can be cultivated on cheap biomass as raw material. There has been very less number of studies directed at this, though there is every possibility that filamentous fungi that are efficient degraders of biomass may harbor such enzymes. The study therefore aimed at isolating a fungus capable of secreting glucose tolerant β- glucosidase enzyme. Production, characterization of β-glucosidases and application of BGL for bioethanol production were attempted.

Extracellular beta-Glucosidase production by marine Aspergillus sydowii BTMFS 55

The beta-glucosidase enzyme purified from the marine fungus, Aspergillus sydowii BTMFS 55 showed a good yield of enzyme production under solid state fermentation. The statistical optimization of the media components revealed that moisture content, concentration of peptone and inoculum are the major parameters which supported the maximal enzyme production. The purified enzyme showed low pH activity and stability, glucose tolerance and activation by ethanol. It could produce ethanol from wheat bran and rice straw by simultaneous saccharification and fermentation with yeast.The glucosidase purified from Aspergillus sydowii BTMFS 55 shows great potential for several biotechnological applications such as the production of bio-ethanol from agricultural biomass and improvement in the aromatic character of wines and fruit juices through the hydrolysis of flavour glucosidic precursors. There is immense scope for the application of this marine fungus in the biofuel production besides in other industries provided further studies are pursued in exploiting this enzyme and the organism particularly scale up studies with respect to application. There is also ample scope for cloning of the gene encoding beta-glucosidase in domesticated hosts such as Pichia pastoris or S. cerevisiae that can produce ethanol directly from cellulosic biomass.

Microwave exfoliated reduced graphene oxide epoxy nanocomposites for high performance applications

Graphene has captured the attention of scientific community due to recently emerging high performance applications. Hence, studying its reinforcing effects on epoxy resin is a significant step. In this study, microwave exfoliated reduced graphene oxide (MERGO) was prepared from natural graphite for subsequent fabrication of epoxy nanocomposites using triethylenetetramine (TETA) as a curing agent via insitu polymerization. Thermogravimetric analysis (TGA), X-ray diffraction (XRD), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), C13 NMR spectroscopy, X-ray photoelectron spectroscopy (XPS) and ultravioletevisible (UVevis) spectroscopy were employed to confirm the simultaneous reduction and exfoliation of graphene oxide. The reinforcing effect of MERGO on epoxy resin was explored by investigating its static mechanical properties and dynamic mechanical analysis (DMA) at MERGO loadings of 0 to 0.5 phr. The micro-structure of epoxy/MERGO nanocomposites was investigated using scanning electron microscope (SEM), transmission electron microscope (TEM) and XRD techniques. The present work reports an enhancement of 32%, 103% and 85% in tensile, impact and flexural strength respectively of epoxy by the addition of even 0.25 phr MERGO. At this loading elastic and flexural moduli also increased by 10% and 65%, respectively. Single-edge-notch three-point-Bending (SEN-TPB) fracture toughness (KIC) measurements were carried out where a 63% increase was observed by the introduction of 0.25 phr MERGO. The interfacial interactions brought about by graphene also benefited the dynamic mechanical properties to a large extent in the form of a significant enhancement in storage modulus and slightly improved glass transition temperature. Considerable improvements were also detected in dielectric properties. The epoxy nanocomposite also attained an ac conductivity of 10 5 S/m and a remarkable increase in dielectric constant. The simple and cost effective way of graphene synthesis for the fabrication of epoxy/MERGO nanocomposites may be extended to the preparation of other MERGO based polymer nanocomposites. This remarkable class of materials has thrown open enormous opportunities for developing conductive adhesives and in microelectronics