Control and application of minimally-actuated underwater vehicles

Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats. With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.

Towards the development of a gas sensor system for monitoring pollutant gases in the low troposphere using small unmanned aerial vehicles

The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.

A general method to determine sampling windows for nonlinear mixed effects models with an application to population pharmacokinetic studies

Optimal design methods have been proposed to determine the best sampling times when sparse blood sampling is required in clinical pharmacokinetic studies. However, the optimal blood sampling time points may not be feasible in clinical practice. Sampling windows, a time interval for blood sample collection, have been proposed to provide flexibility in blood sampling times while preserving efficient parameter estimation. Because of the complexity of the population pharmacokinetic models, which are generally nonlinear mixed effects models, there is no analytical solution available to determine sampling windows. We propose a method for determination of sampling windows based on MCMC sampling techniques. The proposed method attains a stationary distribution rapidly and provides time-sensitive windows around the optimal design points. The proposed method is applicable to determine sampling windows for any nonlinear mixed effects model although our work focuses on an application to population pharmacokinetic models.

Reducing actuator switchings for motion control of autonomous underwater vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.

Wind-energy based path planning for unmanned aerial vehicles using Markov decision processes

Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

An intelligent network control system for plug-in electric vehicles and the associate communication mechanism

The development of an intelligent plug-in electric vehicle (PEV) network is an important research topic in the smart grid environment. An intelligent PEV network enables a flexible control of PEV charging and discharging activities and hence PEVs can be utilized as ancillary service providers in the power system concerned. Given this background, an intelligent PEV network architecture is first developed, and followed by detailed designs of its application layers, including the charging and discharging controlling system, mobility and roaming management, as well as communication mechanisms associated. The presented architecture leverages the philosophy in mobile communication network buildup

Estimating vulnerable windows of exposure to air pollution during pregnancy

Exposure to air pollution during pregnancy is a potential cause of adverse birth outcomes such as preterm birth and stillbirth. The risk of exposure may be greater during vulnerable windows of the pregnancy which might only be weeks long. We demonstrate a method to find these windows based on smoothing the risk of weekly exposure using conditional autoregression. We use incidence density sampling to match cases with adverse birth outcomes to controls whose gestation lasted at least as long as the case. This matching means that cases and controls are have equal length exposure periods, rather than comparing, for example, cases with short gestations to controls with longer gestations. We demonstrate the ability of the method to find vulnerable windows using two simulation studies. We illustrate the method by examining the association between particulate matter air pollution and stillbirth in Brisbane, Australia.

Are academics messy? Testing the broken windows theory with a field experiment in the work environment

We test the broken windows theory using a field experiment in a shared area of an academic workplace(the department common room). More specifically, we explore academics’ and postgraduate students’ behavior under an order condition (a clean environment) and a disorder condition (a messy environment). We find strong evidence that signs of disorderly behavior trigger littering: In 59% of the cases, subjects litter in the disorder treatment as compared to 18% in the order condition. These results remain robust in a multivariate analysis even when controlling for a large set of factors not directly examined by previous studies. Overall, when academic staff and postgraduate students observe that others have violated the social norm of keeping the common room clean, all else being equal, the probability of littering increases by around 40%.

An evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles with tactical and kinematic constraints

This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.

MAVwork : a framework for unified interfacing between micro aerial vehicles and visual controllers

Debugging control software for Micro Aerial Vehicles (MAV) can be risky out of the simulator, especially with professional drones that might harm people around or result in a high bill after a crash. We have designed a framework that enables a software application to communicate with multiple MAVs from a single unified interface. In this way, visual controllers can be first tested on a low-cost harmless MAV and, after safety is guaranteed, they can be moved to the production MAV at no additional cost. The framework is based on a distributed architecture over a network. This allows multiple configurations, like drone swarms or parallel processing of drones' video streams. Live tests have been performed and the results show comparatively low additional communication delays, while adding new functionalities and flexibility. This implementation is open-source and can be downloaded from github.com/uavster/mavwork

Design, simulation and analysis of a parallel hybrid electric propulsion system for unmanned aerial vehicles

Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This paper presents the development of a parallel Hybrid Electric Propulsion System (HEPS) on a small fixed-wing UAV incorporating an Ideal Operating Line (IOL) control strategy. A simulation model of an UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine were determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

Ammonia emissions from a representative in-use fleet of vehicles in Guangzhou

Emission rates of ammonia (NH3) are reported for a fleet of 130 light-, medium-, and heavy-duty vehicles recruited in Guangzhou, China. NH3 measurements were performed using Nessler's Reagents spectrophotometry and nationwide standard chassis dynamometer test cycles required by Chinese EPA. Emissions of CO and NOx were also measured during these test cycles. Emission factors of NH3 were calculated for each type of vehicle and used to estimate the total emissions of NH3 from motor vehicles in Guangzhou (GZ) in 2009. Emission factors of NH3 show large variations among different categories of vehicles, with a range from 4 to 138 mg km-1. The average emissions of NH3 in Guangzhou in 2009 were estimated to be 983 t, with a range from 373 to 2136 t. In addition, it was found that vehicles with the highest NH3 emission rates possess the following characteristics: mediumand heavy-duty vehicles, certified with out-of-date emission standards, mid-range odometer readings, and higher CO and NOx emission rates. The results of this study will be useful for developing NH3 emissions inventories in Guangzhou and other urban areas in China.

Vision based control for micro aerial vehicles : Application to sense and avoid

This work presents a collision avoidance approach based on omnidirectional cameras that does not require the estimation of range between two platforms to resolve a collision encounter. Our method achieves minimum separation between the two vehicles involved by maximising the view-angle given by the omnidirectional sensor. Only visual information is used to achieve avoidance under a bearing- only visual servoing approach. We provide theoretical problem formulation, as well as results from real flights using small quadrotors

Design, modelling and measurement of hybrid powerplant for unmanned aerial vehicles (UAVs)

The success or effectiveness for any aircraft design is a function of many trade-offs. Over the last 100 years of aircraft design these trade-offs have been optimized and dominant aircraft design philosophies have emerged. Pilotless aircraft (or uninhabited airborne systems, UAS) present new challenges in the optimization of their configuration. Recent developments in battery and motor technology have seen an upsurge in the utility and performance of electric powered aircraft. Thus, the opportunity to explore hybrid-electric aircraft powerplant configurations is compelling. This thesis considers the design of such a configuration from an overall propulsive, and energy efficiency perspective. A prototype system was constructed using a representative small UAS internal combustion engine (10cc methanol two-stroke) and a 600W brushless Direct current (BLDC) motor. These components were chosen to be representative of those that would be found on typical small UAS. The system was tested on a dynamometer in a wind-tunnel and the results show an improvement in overall propulsive efficiency of 17% when compared to a non-hybrid powerplant. In this case, the improvement results from the utilization of a larger propeller that the hybrid solution allows, which shows that general efficiency improvements are possible using hybrid configurations for aircraft propulsion. Additionally this approach provides new improvements in operational and mission flexibility (such as the provision of self-starting) which are outlined in the thesis. Specifically, the opportunity to use the windmilling propeller for energy regeneration was explored. It was found (in the prototype configuration) that significant power (60W) is recoverable in a steep dive, and although the efficiency of regeneration is low, the capability can allow several options for improved mission viability. The thesis concludes with the general statement that a hybrid powerplant improves the overall mission effectiveness and propulsive efficiency of small UAS.

An analysis of the KEEP CLEAR pavement markings effects on queuing vehicles dynamic performance at urban signalised intersections

KEEP CLEAR pavement markings are widely used at urban signalised intersections to indicate to drivers to avoid entering blocked intersections. For example, ‘Box junctions’ are most widely used in the United Kingdom and other European countries. However, in Australia, KEEP CLEAR markings are mostly used to improve access from side roads onto a main road, especially when the side road is very close to a signalised intersection. This paper aims to reveal how the KEEP CLEAR markings affect the dynamic performance of the queuing vehicles on the main road, where the side road access is near a signalised intersection. Raw traffic field data was collected from an intersection at the Gold Coast, Australia, and the Kanade–Lucas–Tomasi (KLT) feature tracker approach was used to extract dynamic vehicle data from the raw video footage. The data analysis reveals that the KEEP CLEAR markings generate positive effects on the queuing vehicles in discharge on the main road. This finding refutes the traditional viewpoint that the KEEP CLEAR pavement markings will cause delay for the queuing vehicles’ departure due to the enlarged queue spacing. Further studies are suggested in this paper as well.