The design and intelligent control of an autonomous mobile robot

This thesis presents an investigation into the problems of exploration, map building and collision free navigation for intelligent autonomous mobile robots. The project began with an extensive review of currently available literature in the field of mobile robot research, which included intelligent control techniques and their application. It became clear that there was scope for further development with regard to map building and exploration in new and unstructured environments. Animals have an innate propensity to exhibit such abilities, and so the analogous use of artificial neural networks instead of actual neural systems was examined for use as a method of robot mapping. A simulated behaviour based mobile robot was used in conjunction with a growing cell structure neural network to map out new environments. When using the direct application of this algorithm, topological irregularities were observed to be the direct result of correlations within the input data stream. A modification to this basic system was shown to correct the problem, but further developments would be required to produce a generic solution. The mapping algorithms gained through this approach, although more similar to biological systems, are computationally inefficient in comparison to the methods which were subsequently developed. A novel mapping method was proposed based on the robot creating new location vectors, or nodes, when it exceeded a distance threshold from its mapped area. Network parameters were developed to monitor the state of growth of the network and aid the robot search process. In simulation, the combination of the novel mapping and search process were shown to be able to construct maps which could be subsequently used for collision free navigation. To develop greater insights into the control problem and to validate the simulation work the control structures were ported to a prototype mobile robot. The mobile robot was of circular construction, with a synchro-drive wheel configuration, and was equipped with eight ultrasonic distance sensors and an odometric positioning system. It was self-sufficient, incorporating all its power and computational resources. The experiments observed the effects of odometric drift and demonstrated methods of re-correction which were shown to be effective. Both the novel mapping method, and a new algorithm based on an exhaustive mesh search, were shown to be able to explore different environments and subsequently achieve collision free navigation. This was shown in all cases by monitoring the estimates in the positional error which remained within fixed bounds

An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions

Today\u27s predominantly-employed signature-based intrusion detection systems are reactive in nature and storage-limited. Their operation depends upon catching an instance of an intrusion or virus after a potentially successful attack, performing post-mortem analysis on that instance and encoding it into a signature that is stored in its anomaly database. The time required to perform these tasks provides a window of vulnerability to DoD computer systems. Further, because of the current maximum size of an Internet Protocol-based message, the database would have to be able to maintain 25665535 possible signature combinations. In order to tighten this response cycle within storage constraints, this thesis presents an Artificial Immune System-inspired Multiobjective Evolutionary Algorithm intended to measure the vector of trade-off solutions among detectors with regard to two independent objectives: best classification fitness and optimal hypervolume size. Modeled in the spirit of the human biological immune system and intended to augment DoD network defense systems, our algorithm generates network traffic detectors that are dispersed throughout the network. These detectors promiscuously monitor network traffic for exact and variant abnormal system events, based on only the detector\u27s own data structure and the ID domain truth set, and respond heuristically. The application domain employed for testing was the MIT-DARPA 1999 intrusion detection data set, composed of 7.2 million packets of notional Air Force Base network traffic. Results show our proof-of-concept algorithm correctly classifies at best 86.48% of the normal and 99.9% of the abnormal events, attributed to a detector affinity threshold typically between 39-44%. Further, four of the 16 intrusion sequences were classified with a 0% false positive rate

Design, Implementation, and Verification of a Reactor Protection System Using HFC6000

Recently, a nuclear power plant physical simulator to support instrumentation and control (I&C) research has been constructed at the University of Western Ontario using industry-grade sensors and actuators. This platform, known as the Nuclear Power Control Test Facility (NPCTF), provides means to safely inject faults and examine their effects on the system. The NPCTF may be configured into a number of nuclear power plant (NPP) types, but focus has been placed on CANadian Deuterium Uranium (CANDU) type. In a CANDU based NPP, there are two independent and separated systems with decision-making units capable of actuating two shutdown systems. These units form the reactor protection system, and monitor critical system variables to ensure that they remain within safe operating limits. For this work, in ongoing efforts to further improve the fidelity of the NPCTF, a dedicated reactor protection system has been realized. This system has been implemented through a United States Nuclear Regulatory Commision certified safety programmable logic controller (PLC), known as the HFC6000. This has been integrated with the NPCTF through a standard industrial interface, and performs monitoring functions and decision logic operations. The reactor protection system responds to contingencies by issuing trip signals to perform safety shutdown actions. The designed system has undergone a full verification and validation (V&V) process. Nine CNSC design basis events have been considered under full-system testing, including the loss-of-coolant-accident and loss-of-reactor-control. The designed logic achieved a 100% success rate on 25 trials. Further, the implemented system produced no spurious trips during normal operations. The relationship between CANDU type NPPs and the NPCTF has been established. The work has also concluded that the NPCTF is capable of replicating dynamic relationships among different variables in an NPP. Through V&V tests,, the designed logic, and implemented system using HFC6000 have been proven to be successful according to the safety system criteria from the Canadian Nuclear Safety Commission

Radiation detectors and sources enhanced with micro/nanotechnology

The ongoing threat of nuclear terrorism presents major challenges to maintaining national security. Currently, only a small percentage of the cargo containers that enter America are searched for fissionable bomb making materials. This work reports on a multi-channel radiation detection platform enabled with nanoparticles that is capable of detecting and discriminating all types of radiation emitted from fissionable bomb making materials. Typical Geiger counters are limited to detecting only beta and gamma radiation. The micro-Geiger counter reported here detects all species of radiation including beta particles, gamma/X-rays, alpha particles, and neutrons. The multi-species detecting micro-Geiger counter contains a hermetically sealed and electrically biased fill gas. Impinging radiation interacts with tailored nanoparticles to release secondary charged particles that ionize the fill gas. The ionized particles collect on respectively biased electrodes resulting in a characteristic electrical pulse. Pulse height spectroscopy and radiation energy binning techniques can then be used to analyze the pulses to determine the specific radiation isotope. The ideal voltage range of operation for energy discrimination was found to be in the proportional region at 1000VDC. In this region, specific pulse heights for different radiation species resulted. The amplification region strength which determines the device sensitivity to radiation energy can be tuned with the electrode separation distance. Considerable improvements in count rates were achieved by using the charge conversion nanoparticles with the highest cross sections for particular radiation species. The addition of tungsten nanoparticles to the microGeiger counter enabled the device to be four times more efficient at detecting low level beta particles with a dose rate of 3.2uR/hr (micro-Roentgen per hour) and just under three times more efficient than an off the shelf Geiger counter. The addition of lead nanoparticles enabled the gamma/X-ray microGeiger counter channel to be 28 times more efficient at detecting low level gamma rays with a dose rate of 10uR/hr when compared to a device without nanoparticles. The addition of 10B nanoparticles enabled the neutron microGeiger counter channel to be 17 times more efficient at detecting neutrons. The device achieved a neutron count rate of 9,866 counts per minute when compared to a BF3 tube which resulted in a count rate of 9,000 counts per minute. By using a novel micro-injection ceramic molding and low temperature (950°C) silver paste metallizing process, the batch fabrication of essentially disposable micro-devices can be achieved. This novel fabrication technique was then applied to a MEMS neutron gun and water spectroscopy device that also utilizes the high voltage/temperature insulating packaging

The hardware implementation of an artificial neural network using stochastic pulse rate encoding principles

In this thesis the development of a hardware artificial neuron device and artificial neural network using stochastic pulse rate encoding principles is considered. After a review of neural network architectures and algorithmic approaches suitable for hardware implementation, a critical review of hardware techniques which have been considered in analogue and digital systems is presented. New results are presented demonstrating the potential of two learning schemes which adapt by the use of a single reinforcement signal. The techniques for computation using stochastic pulse rate encoding are presented and extended with new novel circuits relevant to the hardware implementation of an artificial neural network. The generation of random numbers is the key to the encoding of data into the stochastic pulse rate domain. The formation of random numbers and multiple random bit sequences from a single PRBS generator have been investigated. Two techniques, Simulated Annealing and Genetic Algorithms, have been applied successfully to the problem of optimising the configuration of a PRBS random number generator for the formation of multiple random bit sequences and hence random numbers. A complete hardware design for an artificial neuron using stochastic pulse rate encoded signals has been described, designed, simulated, fabricated and tested before configuration of the device into a network to perform simple test problems. The implementation has shown that the processing elements of the artificial neuron are small and simple, but that there can be a significant overhead for the encoding of information into the stochastic pulse rate domain. The stochastic artificial neuron has the capability of on-line weight adaption. The implementation of reinforcement schemes using the stochastic neuron as a basic element are discussed

Extension and hardware implementation of the comprehensive integrated security system concept

Merged with duplicate record (10026.1/700) on 03.01.2017 by CS (TIS)This is a digitised version of a thesis that was deposited in the University Library. If you are the author please contact PEARL Admin ([email protected]) to discuss options.The current strategy to computer networking is to increase the accessibility that legitimate users have to their respective systems and to distribute functionality. This creates a more efficient working environment, users may work from home, organisations can make better use of their computing power. Unfortunately, a side effect of opening up computer systems and placing them on potentially global networks is that they face increased threats from uncontrolled access points, and from eavesdroppers listening to the data communicated between systems. Along with these increased threats the traditional ones such as disgruntled employees, malicious software, and accidental damage must still be countered. A comprehensive integrated security system ( CISS ) has been developed to provide security within the Open Systems Interconnection (OSI) and Open Distributed Processing (ODP) environments. The research described in this thesis investigates alternative methods for its implementation and its optimisation through partial implementation within hardware and software and the investigation of mechanismsto improve its security. A new deployment strategy for CISS is described where functionality is divided amongst computing platforms of increasing capability within a security domain. Definitions are given of a: local security unit, that provides terminal security; local security servers that serve the local security units and domain management centres that provide security service coordination within a domain. New hardware that provides RSA and DES functionality capable of being connected to Sun microsystems is detailed. The board can be used as a basic building block of CISS, providing fast cryptographic facilities, or in isolation for discrete cryptographic services. Software written for UNIX in C/C++ is described, which provides optimised security mechanisms on computer systems that do not have SBus connectivity. A new identification/authentication mechanism is investigated that can be added to existing systems with the potential for extension into a real time supervision scenario. The mechanism uses keystroke analysis through the application of neural networks and genetic algorithms and has produced very encouraging results. Finally, a new conceptual model for intrusion detection capable of dealing with real time and historical evaluation is discussed, which further enhances the CISS concept

Research summary, January 1989 - June 1990

The Research Institute for Advanced Computer Science (RIACS) was established at NASA ARC in June of 1983. RIACS is privately operated by the Universities Space Research Association (USRA), a consortium of 62 universities with graduate programs in the aerospace sciences, under a Cooperative Agreement with NASA. RIACS serves as the representative of the USRA universities at ARC. This document reports our activities and accomplishments for the period 1 Jan. 1989 - 30 Jun. 1990. The following topics are covered: learning systems, networked systems, and parallel systems

An ultra low power implantable neural recording system for brain-machine interfaces

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 179-187).In the past few decades, direct recordings from different areas of the brain have enabled scientists to gradually understand and unlock the secrets of neural coding. This scientific advancement has shown great promise for successful development of practical brain-machine interfaces (BMIs) to restore lost body functions to patients with disorders in the central nervous system. Practical BMIs require the uses of implantable wireless neural recording systems to record and process neural signals, before transmitting neural information wirelessly to an external device, while avoiding the risk of infection due to through-skin connections. The implantability requirement poses major constraints on the size and total power consumption of the neural recording system. This thesis presents the design of an ultra-low-power implantable wireless neural recording system for use in brain-machine interfaces. The system is capable of amplifying and digitizing neural signals from 32 recording electrodes, and processing the digitized neural data before transmitting the neural information wirelessly to a receiver at a data rate of 2.5 Mbps. By combining state-of-the-art custom ASICs, a commercially-available FPGA, and discrete components, the system achieves excellent energy efficiency, while still offering design flexibility during the system development phase. The system's power consumption of 6.4 mW from a 3.6-V supply at a wireless output data rate of 2.5 Mbps makes it the most energy-efficient implantable wireless neural recording system reported to date. The system is integrated on a flexible PCB platform with dimensions of 1.8 cm x 5.6 cm and is designed to be powered by an implantable Li-ion battery. As part of this thesis, I describe the design of low-power integrated circuits (ICs) for amplification and digitization of the neural signals, including a neural amplifier and a 32-channel neural recording IC. Low-power low-noise design techniques are utilized in the design of the neural amplifier such that it achieves a noise efficiency factor (NEF) of 2.67, which is close to the theoretical limit determined by physics. The neural recording IC consists of neural amplifiers, analog multiplexers, ADCs, serial programming interfaces, and a digital processing unit. It can amplify and digitize neural signals from 32 recording electrodes, with a sampling rate of 31.25 kS/s per channel, and send the digitized data off-chip for further processing. The IC was successfully tested in an in-vivo wireless recording experiment from a behaving primate with an average power dissipation per channel of 10.1 [mu]W. Such a system is also widely useful in implantable brain-machine interfaces for the blind and paralyzed, and in cochlea implants for the deaf.by Woradorn Wattanapanitch.Ph.D

Generating Circuit Tests by Exploiting Designed Behavior

This thesis describes two programs for generating tests for digital circuits that exploit several kinds of expert knowledge not used by previous approaches. First, many test generation problems can be solved efficiently using operation relations, a novel representation of circuit behavior that connects internal component operations with directly executable circuit operations. Operation relations can be computed efficiently by searching traces of simulated circuit behavior. Second, experts write test programs rather than test vectors because programs are more readable and compact. Test programs can be constructed automatically by merging program fragments using expert-supplied goal-refinement rules and domain-independent planning techniques