Optimal mission path planning (MPP) for an air sampling unmanned aerial system

This paper presents advanced optimization techniques for Mission Path Planning (MPP) of a UAS fitted with a spore trap to detect and monitor spores and plant pathogens. The UAV MPP aims to optimise the mission path planning search and monitoring of spores and plant pathogens that may allow the agricultural sector to be more competitive and more reliable. The UAV will be fitted with an air sampling or spore trap to detect and monitor spores and plant pathogens in remote areas not accessible to current stationary monitor methods. The optimal paths are computed using a Multi-Objective Evolutionary Algorithms (MOEAs). Two types of multi-objective optimisers are compared; the MOEA Non-dominated Sorting Genetic Algorithms II (NSGA-II) and Hybrid Game are implemented to produce a set of optimal collision-free trajectories in three-dimensional environment. The trajectories on a three-dimension terrain, which are generated off-line, are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different position with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of coupling a Hybrid-Game strategy to a MOEA for MPP tasks. The reduction of numerical cost is an important point as the faster the algorithm converges the better the algorithms is for an off-line design and for future on-line decisions of the UAV.

Evaluation of distributed control signaling protocols in GMPLS

GMPLS is a generalized form of MPLS (MultiProtocol Label Switching). MPLS is IP packet based and it uses MPLS-TE for Packet Traffic Engineering. GMPLS is extension to MPLS capabilities. It provides separation between transmission, control and management plane and network management. Control plane allows various applications like traffic engineering, service provisioning, and differentiated services. GMPLS control plane architecture includes signaling (RSVP-TE, CR-LDP) and routing (OSPF-TE, ISIS-TE) protocols. This paper provides an overview of the signaling protocols, describes their main functionalities, and provides a general evaluation of both the protocols.

Networked robots : flying robot navigation using a sensor net

This paper introduces the application of a sensor network to navigate a flying robot. We have developed distributed algorithms and efficient geographic routing techniques to incrementally guide one or more robots to points of interest based on sensor gradient fields, or along paths defined in terms of Cartesian coordinates. The robot itself is an integral part of the localization process which establishes the positions of sensors which are not known a priori. We use this system in a large-scale outdoor experiment with Mote sensors to guide an autonomous helicopter along a path encoded in the network. A simple handheld device, using this same environmental infrastructure, is used to guide humans.

UAS Mission Path Planning System, (MPPS) using hybrid-game coupled to multi-objective optimizer

This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.

A synthesizable hardware evolutionary algorithm design for unmanned aerial system real-time path planning

The main objective of this paper is to detail the development of a feasible hardware design based on Evolutionary Algorithms (EAs) to determine flight path planning for Unmanned Aerial Vehicles (UAVs) navigating terrain with obstacle boundaries. The design architecture includes the hardware implementation of Light Detection And Ranging (LiDAR) terrain and EA population memories within the hardware, as well as the EA search and evaluation algorithms used in the optimizing stage of path planning. A synthesisable Very-high-speed integrated circuit Hardware Description Language (VHDL) implementation of the design was developed, for realisation on a Field Programmable Gate Array (FPGA) platform. Simulation results show significant speedup compared with an equivalent software implementation written in C++, suggesting that the present approach is well suited for UAV real-time path planning applications.

Practical application of pseudospectral optimization to robot path planning

To obtain minimum time or minimum energy trajectories for robots it is necessary to employ planning methods which adequately consider the platform’s dynamic properties. A variety of sampling, graph-based or local receding-horizon optimisation methods have previously been proposed. These typically use simplified kino-dynamic models to avoid the significant computational burden of solving this problem in a high dimensional state-space. In this paper we investigate solutions from the class of pseudospectral optimisation methods which have grown in favour amongst the optimal control community in recent years. These methods have high computational efficiency and rapid convergence properties. We present a practical application of such an approach to the robot path planning problem to provide a trajectory considering the robot’s dynamic properties. We extend the existing literature by augmenting the path constraints with sensed obstacles rather than predefined analytical functions to enable real world application.

Modeling circulation of train-set with multiple routing

Planning on utilization of train-set is one of the key tasks of transport organization for passenger dedicated railway in China. It also has strong relationships with timetable scheduling and operation plans at a station. To execute such a task in a railway hub pooling multiple railway lines, the characteristics of multiple routing for train-set is discussed in term of semicircle of train-sets' turnover. In programming the described problem, the minimum dwell time is selected as the objectives with special derive constraints of the train-set's dispatch, the connecting conditions, the principle of uniqueness for train-sets, and the first plus for connection in the same direction based on time tolerance σ. A compact connection algorithm based on time tolerance is then designed. The feasibility of the model and the algorithm is proved by the case study. The result indicates that the circulation model and algorithm about multiple routing can deal with the connections between the train-sets of multiple directions, and reduce the train's pulling in or leaving impact on the station's throat.

Creative China must find its own path

Rather than catch-up with the West, when it comes to creative industries, China must find its own path.

Path planning, guidance and control for a UAV forced landing

A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

Bricolage as a path to innovation for resource constrained new firms

Evidence suggests that both start-up and young firms (henceforth: new firms) – despite typically being resource-constrained – are sometimes able to innovate (Katila & Shane 2005). Such firms are seldom able to invest in expensive innovation processes, which suggests that they may rely on other pathways to innovation. In this paper, we test arguments that “bricolage,” defined as making do by applying combinations of the resources at hand to new problems and opportunities, provides a pathway to innovation for new firms. Our results suggest that variations in bricolage behaviors can provide an explanation of innovation under resource constraints by new firms.

The influence of sensitivity to reward and punishment, propensity for sensation seeking, depression, and anxiety on the risky behaviour of novice drivers : a path model

Young novice drivers are significantly more likely to be killed or injured in car crashes than older, experienced drivers. Graduated driver licensing (GDL), which allows the novice to gain driving experience under less-risky circumstances, has resulted in reduced crash incidence; however, the driver's psychological traits are ignored. This paper explores the relationships between gender, age, anxiety, depression, sensitivity to reward and punishment, sensation-seeking propensity, and risky driving. Participants were 761 young drivers aged 17–24 (M= 19.00, SD= 1.56) with a Provisional (intermediate) driver's licence who completed an online survey comprising socio-demographic questions, the Impulsive Sensation Seeking Scale, Kessler's Psychological Distress Scale, the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, and the Behaviour of Young Novice Drivers Scale. Path analysis revealed depression, reward sensitivity, and sensation-seeking propensity predicted the self-reported risky behaviour of the young novice drivers. Gender was a moderator; and the anxiety level of female drivers also influenced their risky driving. Interventions do not directly consider the role of rewards and sensation seeking, or the young person's mental health. An approach that does take these variables into account may contribute to improved road safety outcomes for both young and older road users.

Aircraft emission reduction through multi-disciplinary flight path optimisation

There is worldwide interest in reducing aircraft emissions. The difficulty of reducing emissions including water vapour, carbon dioxide (CO2) and oxides of nitrogen (NOx) is mainly due from the fact that a commercial aircraft is usually designed for a particular optimal cruise altitude but may be requested or required to operate and deviate at different altitude and speeds to archive a desired or commanded flight plan, resulting in increased emissions. This is a multi- disciplinary problem with multiple trade-offs such as optimising engine efficiency, minimising fuel burnt, minimise emissions while maintaining aircraft separation and air safety. This project presents the coupling of an advanced optimisation technique with mathematical models and algorithms for aircraft emission reduction through flight optimisation. Numerical results show that the method is able to capture a set of useful trade-offs between aircraft range and NOx, and mission fuel consumption and NOx. In addition, alternative cruise operating conditions including Mach and altitude that produce minimum NOx and CO2 (minimum mission fuel weight) are suggested.

Surrogacy - A Path of Obstacles

Surrogacy has become an effective and accepted form of reproductive technology. It enables couples, regardless of gender or sexuality, to achieve the dream of becoming a parent in circumstances where other forms of reproductive technology and adoption are either not possible or have failed. To its credit, the Queensland parliament has recently brought this state up to date by enacting surrogacy laws that are in line with the majority of statutes implemented throughout the country. The Surrogacy Act 2010 (Qld) allows for the court to make a parentage order in certain circumstances where parties have entered into a surrogacy arrangement. A parentage order effectively transfers parental rights from the birth mother (and her spouse or de facto if there is one) to the intended parents. The requirements which must be satisfied to obtain a parenting order are comprehensive and onerous, making the path to parenthood through a surrogacy arrangement by no means easy. At the heart of the surrogacy issue lies a question, the answer to which has shifted and continues to shift as reproductive technologies continue to increase in success, method and popularity - what is a parent? A recent decision of the Administrative Appeals Tribunal, Hudson v Minister for Immigration and Citizenship, brought to attention the meaning of the word ‘parent’ as it appears in s 16(2) Australian Citizenship Act 2007 (Cth) (‘the Act’). Section 16(2) deals with citizenship by descent and provides that a person born outside Australia may make an application to the Minister to become an Australian citizen if a parent of the person was an Australian citizen at the time of the birth.

Path planning using surface shape and ground properties

This paper presents a path planning technique for ground vehicles that accounts for the dynamics of the vehicle, the topography of the terrain and the wheel/ground interaction properties such as friction. The first two properties can be estimated using well known sensors and techniques, but the third is not often estimated even though it has a significant effect on the motion of a high-speed vehicle. We introduce a technique which allows the estimation of wheel slip from which frictional parameters can be inferred. We present simulation results which show the importance of modelling topography and ground properties and experimental results which show how ground properties can be estimated along a 350m outdoor traverse.