Accurate Indoor Positioning of Firefighters using Dual Foot-mounted Inertial Sensors and Inter-agent Ranging

A real-time cooperative localization system, utilizing dual foot-mounted low-cost inertial sensors and RF-based inter-agent ranging, has been developed. Scenario-based tests have been performed, using fully-equipped firefighters mimicking a search operation in a partly smoke-filled environment, to evaluate the performance of the TOR (Tactical lOcatoR) system. The performed tests included realistic firefighter movements and inter-agent distances, factors that are crucial in order to provide realistic evaluations of the expected performance in real-world operations. The tests indicate that the TOR system may be able to provide a position accuracy of approximately two to three meters during realistic firefighter operations, with only two smoke diving firefighters and one supervising firefighter within range.

Optomechanical Inertial Sensors and Feedback Cooling

The optomechanical interaction is an extremely powerful tool with which to measure mechanical motion. The displacement resolution of chip-scale optomechanical systems has been measured on the order of 1⁄10th of a proton radius. So strong is this optomechanical interaction that it has recently been used to remove almost all thermal noise from a mechanical resonator and observe its quantum ground-state of motion starting from cryogenic temperatures.

In this work, chapter 1 describes the basic physics of the canonical optomechanical system, optical measurement techniques, and how the optomechanical interaction affects the coupled mechanical resonator. In chapter 2, we describe our techniques for realizing this canonical optomechanical system in a chip-scale form factor.

In chapter 3, we describe an experiment where we used radiation pressure feedback to cool a mesoscopic mechanical resonator near its quantum ground-state from room-temperature. We cooled the resonator from a room temperature phonon occupation of <n> = 6.5 million to an occupation of <n> = 66, which means the resonator is in its ground state approximately 2% of the time, while being coupled to a room-temperature thermal environment. At the time of this work, this is the closest a mesoscopic mechanical resonator has been to its ground-state of motion at room temperature, and this work begins to open the door to room-temperature quantum control of mechanical objects.

Chapter 4 begins with the realization that the displacement resolutions achieved by optomechanical systems can surpass those of conventional MEMS sensors by an order of magnitude or more. This provides the motivation to develop and calibrate an optomechanical accelerometer with a resolution of approximately 10 micro-g/rt-Hz over a bandwidth of approximately 30 kHz. In chapter 5, we improve upon the performance and practicality of this sensor by greatly increasing the test mass size, investigating and reducing low-frequency noise, and incorporating more robust optical coupling techniques and capacitive wavelength tuning. Finally, in chapter 6 we present our progress towards developing another optomechanical inertial sensor - a gyroscope.

Robust Agent Control of an Autonomous Robot with Many Sensors and Actuators

This thesis presents methods for implementing robust hexpod locomotion on an autonomous robot with many sensors and actuators. The controller is based on the Subsumption Architecture and is fully distributed over approximately 1500 simple, concurrent processes. The robot, Hannibal, weighs approximately 6 pounds and is equipped with over 100 physical sensors, 19 degrees of freedom, and 8 on board computers. We investigate the following topics in depth: distributed control of a complex robot, insect-inspired locomotion control for gait generation and rough terrain mobility, and fault tolerance. The controller was implemented, debugged, and tested on Hannibal. Through a series of experiments, we examined Hannibal's gait generation, rough terrain locomotion, and fault tolerance performance. These results demonstrate that Hannibal exhibits robust, flexible, real-time locomotion over a variety of terrain and tolerates a multitude of hardware failures.

Trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms: a model-based framework

Evaluation of temperature distribution in cold rooms is an important consideration in the design of food storage solutions. Two common approaches used in both industry and academia to address this question are the deployment of wireless sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld evaluation of temperature distribution in a cold room, both approaches have their limitations. For wireless sensors, it is economically unfeasible to carry out large-scale deployment (to obtain a high resolution of temperature distribution); while with CFD modelling, it is usually not accurate enough to get a reliable result. In this paper, we propose a model-based framework which combines the wireless sensors technique with CFD modelling technique together to achieve a satisfactory trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms. A case study is presented to demonstrate the usability of the framework.

Multicomponent gas-mixture measurements using an array of gas sensors and an artificial neural-network

An Electronic Nose is being jointly developed between the University of Greenwich and the Institute of Intelligent Machines to detect the gases given off from an oil filled transformer when it begins to break down. The gas sensors being used are very simple, consisting of a layer of Tin Oxide (SnO2) which is heated to approximately 640 K and the conductivity varies with the gas concentrations. Some of the shortcomings introduced by the commercial gas sensors available are being overcome by the use of an integrated array of gas sensors and the use of artificial neural networks which can be 'taught' to recognize when the gas contains several components. At present simulated results have achieved up to a 94% success rate of recognizing two component gases and future work will investigate alternative neural network configurations to maintain this success rate with practical measurements.

Solid phase velocity measurements utilising electrostatic sensors and cross correlation signal processing

Gas-solids two phase systems are widely employed within process plant in the form of pneumatic conveyors, dust extraction systems and solid fuel injection systems. The measurement of solids phase velocity therefore has wide potential application in flow monitoring and, in conjunction with density measurement instrumentation, solids mass flow rate measurement. Historically, a number of authors have detailed possible measurement techniques, and some have published limited test results. It is, however, apparent that none of these technologies have found wide application in industry. Solids phase velocity measurements were undertaken using real time cross correlation of signals from two electrostatic sensors spaced axially along a pipeline conveying pulverised coal (PF). Details of the measurement equipment, the pilot scale test rig and the test results are presented.

Electrical Based Sensors and Remote Monitoring System for Assessing the Corrosion Related Activity in Concrete at Hangzhou Bay Bridge

Concrete structures in marine environments are subjected to cyclic wetting and drying, corrosion of reinforcement due to chloride ingress and biological deterioration. In order to assess the quality of concrete and predict the corrosion activity of reinforcing steel in concrete in this environment, it is essential to monitor the concrete continuously right from the construction phase to the end of service life of the structure. In this paper a novel combination of sensor techniques which are integrated in a sensor probe is used to monitor the quality of cover concrete and corrosion of the reinforcement. The integrated sensor probe was embedded in different concrete samples exposed to an aggressive marine environment at the Hangzhou Bay Bridge in China. The sensor probes were connected to a monitoring station, which enabled the access and control of the data remotely from Belfast, UK. The initial data obtained from the monitoring station reflected the early age properties of the concretes and distinct variations in these properties were observed with different concrete types.