Long-term Informative Path Planning with Autonomous Soaring

The ability of UAVs to cover large areas efficiently is valuable for information gathering missions. For long-term information gathering, a UAV may extend its endurance by accessing energy sources present in the atmosphere. Thermals are a favourable source of wind energy and thermal soaring is adopted in this thesis to enable long-term information gathering. This thesis proposes energy-constrained path planning algorithms for a gliding UAV to maximise information gain given a mission time that greatly exceeds the UAV's endurance. This thesis is motivated by the problem of probabilistic target-search performed by an energy-constrained UAV, which is tasked to simultaneously search for a lost ground target and explore for thermals to regain energy. This problem is termed informative soaring (IFS) and combines informative path planning (IPP) with energy constraints. IFS is shown to be NP-hard by showing that it has a similar problem structure to the weight-constrained shortest path problem with replenishments. While an optimal solution may not exist in polynomial time, this thesis proposes path planning algorithms based on informed tree search to find high quality plans with low computational cost. This thesis addresses complex probabilistic belief maps and three primary contributions are presented: • First, IFS is formulated as a graph search problem by observing that any feasible long-term plan must alternate between 1) information gathering between thermals and 2) replenishing energy within thermals. This is a first step to reducing the large search state space. • The second contribution is observing that a complex belief map can be viewed as a collection of information clusters and using a divide and conquer approach, cluster tree search (CTS), to efficiently find high-quality plans in the large search state space. In CTS, near-greedy tree search is used to find locally optimal plans and two global planning versions are proposed to combine local plans into a full plan. Monte Carlo simulation studies show that CTS produces similar plans to variations of exhaustive search, but runs five to 20 times faster. The more computationally efficient version, CTSDP, uses dynamic programming (DP) to optimally combine local plans. CTSDP is executed in real time on board a UAV to demonstrate computational feasibility. • The third contribution is an extension of CTS to unknown drifting thermals. A thermal exploration map is created to detect new thermals that will eventually intercept clusters, and therefore be valuable to the mission. Time windows are computed for known thermals and an optimal cluster visit schedule is formed. A tree search algorithm called CTSDrift combines CTS and thermal exploration. Using 2400 Monte Carlo simulations, CTSDrift is evaluated against a Full Knowledge method that has full knowledge of the thermal field and a Greedy method. On average, CTSDrift outperforms Greedy in one-third of trials, and achieves similar performance to Full Knowledge when environmental conditions are favourable

Young frigatebirds learn how to compensate for wind-drift

Compensating for wind drift can improve goalward flight efficiency in animal taxa, especially amongst those that rely on thermal soaring to travel large distances. Little is known, however, about how animals acquire this ability. The great frigatebird (Fregata minor) exemplifies the challenges of wind drift compensation because it lives a highly pelagic lifestyle, travelling very long distances over the open ocean but without the ability to land on water. Using GPS tracks from fledgling frigatebirds, we followed young frigatebirds from the moment of fledging to investigate whether wind drift compensation was learnt and, if so, what sensory inputs underpinned it. We found that the effect of wind drift reduced significantly with both experience and access to visual landmark cues. Further, we found that the effect of experience on wind drift compensation was more pronounced when birds were out-of-sight of land. Our results suggest that improvement in wind drift compensation is not solely the product of either physical maturation or general improvements in flight control. Instead, we believe it is likely that they reflect how frigatebirds learn to process sensory information so as to reduce wind drift and maintain a constant course during goalward movement

The real issue is flying, not death. Dealing with risk in the subculture of Italian gliding

This thesis aims to rethink subcultural theory by applying it to an unusual age bracket. It proposes to chart forms of reflexivity in risk perception among the practitioners of a dangerous sport, and adopts as its empirical point of departure the subculture of middle class, middle-aged glider pilots in the Italian village of Bilonia. Exploring the world of gliding, it describes ethnographically the local situations in two gliding clubs, Bilonia, where the main fieldwork took place, and Piti, where a second shorter period of participant-observation was conducted. Adopting a comparative perspective, these local realities are contrasted amongst themselves and with the wider subculture of gliding in Italy. The thesis argues that, despite the prevalence of a single dominant subculture, gliding is practised in different ways in different places, especially with regard to risk perception and management. However, these are affected in all locations by the peculiar characteristic of the subculture, the average age of the glider pilots, which rules out the extreme behaviours of younger practitioners and goes against the tenets of some explanations of voluntary risk taking. In the first three chapters a theoretical framework is developed based upon advances in sports anthropology, subcultural theory and social scientific theories of risk. In the empirical chapters that follow, gliding is variously introduced as an experience involving a precise script, as a local reality tinged with peculiarities that set it apart from the wider reality of the sport in the national arena. The last three chapters discuss key points of the theoretical approach adopted and the findings they led to, in particular the implications for the study of sport subcultures. The empirical data presented suggest the existence of a middle-aged sport subculture, something that has not often been encountered in the literature on the subject. It is shown how risk perception follows a precise pattern which is shaped by the cultural norm of the gliding subculture – in its turn affected by the average age of the members

Fly with the flock: immersive solutions for animal movement visualization and analytics

Understanding the movement of animals is important for a wide range of scientific interests including migration, disease spread, collective movement behaviour and analysing motion in relation to dynamic changes of the environment such as wind and thermal lifts. Particularly, the three-dimensional (3D) spatial–temporal nature of bird movement data, which is widely available with high temporal and spatial resolution at large volumes, presents a natural option to explore the potential of immersive analytics (IA). We investigate the requirements and benefits of a wide range of immersive environments for explorative visualization and analytics of 3D movement data, in particular regarding design considerations for such 3D immersive environments, and present prototypes for IA solutions. Tailored to biologists studying bird movement data, the immersive solutions enable geo-locational time-series data to be investigated interactively, thus enabling experts to visually explore interesting angles of a flock and its behaviour in the context of the environment. The 3D virtual world presents the audience with engaging and interactive content, allowing users to ‘fly with the flock’, with the potential to ascertain an intuitive overview of often complex datasets, and to provide the opportunity thereby to formulate and at least qualitatively assess hypotheses. This work also contributes to ongoing research efforts to promote better understanding of bird migration and the associated environmental factors at the global scale, thereby providing a visual vehicle for driving public awareness of environmental issues and bird migration patterns

Northern gannet Morus bassanus foraging ecology: A multidimensional approach

This thesis brings together multiple strands of information at different temporal and spatial scales to shed new light on foraging behaviour. Foraging accounts for much of the time and energy budgets of wild animals and underpins many ecological and evolutionary processes. I used the central place foraging trips of a wide-ranging marine predator, the northern gannet Morus bassanus, as a model to study foraging ecology and the influences of fisheries and climate change. My five data chapters span a range of temporal scales, from two-second behavioural classification to interannual variation across 11 years, as well as a range of spatial scales from individual bird-boat interactions to a multi-colony comparison spanning 83% of the latitudinal range of breeding colonies. First, I found sex-specific foraging behaviour across a range of spatial, temporal and isotopic axes and that the extent of segregation varied inter-annually. Second, I examined the energetics of foraging behaviour, revealing the relative costs of different behaviours and how they relate to three-dimensional flight patterns. I found that effort was driven by the time spent performing behaviours rather than differences in the costs of behaviours per unit time. Furthermore, the proportions of each trip spent performing each behaviour were independent of trip length, meaning that foraging trip duration was a good metric of overall effort. Third, I used bird-borne videos cameras to reveal a high incidence of gannets scavenging from fisheries discards and trawl nets in the Celtic Sea. Scavenging is often thought to be an energy-saving strategy, but the energetic cost of scavenging was no different from that of natural foraging. Fourth, I found that gannets did not respond to nearby fishing vessels in Iceland, where discarding is banned and foraging effort suggested plentiful natural prey. Finally, I collated a large multi-colony dataset, which showed that foraging range and trip durations decreased with latitude when controlling for colony size. I related this pattern to poleward range shifting in response to climate change. Overall, I found that foraging behaviour is highly variable in some respects and consistent in others. This is driven by stable factors such as sex and colony location and changing factors such as population size, climate and oceanography, and fisheries practice or policy. This thesis particularly highlights the benefits of combining data from multiple sources, time periods and regions in order to reveal new patterns.Natural Environment Research Council (NERC

Remotely sensing motion: the use of multiple biologging technologies to detect fine-scale, at-sea behaviour of breeding seabirds in a variable Southern Ocean environment

The at-sea behaviour of seabirds, such as albatrosses and petrels (order Procellariiformes), is difficult to study because they spend most of their time on the ocean and have extremely large ranges. In the early 2000s, behavioural studies of seabirds were dominated by diving patterns of diving birds or spatial studies from satellite telemetry. Recent advances in biologging technologies have opened up new avenues for studying the at-sea behaviour of farranging seabirds in their natural environment. Bio-logging devices are now small enough to be attached to flying seabirds where multiple sensors record data at infrasecond sampling rates. These data can be used to infer, inter alia, body posture, activity (e.g. flapping, takeoff, landing, etc.), magnetic heading and spatial distribution at a resolution that was not previously possible. Bio-logging devices are battery powered and a tradeoff exists between the length of deployments and sampling frequencies, however not a lot of study has been done on what the effect of coarse sampling rates are on data quality. Together with the masses of data that are generated by bio-logging devices, analytical tools have also become available to extract useful metrics from the data. This thesis utilized some of the latest bio-logging technology to study the at-sea behaviour of several procellariiforms, breeding on Marion, Gough and Nightingale Islands, from finescale data. After describing the loggers used and the methods of deployment in Chapter 2, I assess the effect that sampling rates have on metrics derived from GPS loggers in Chapter 3. This was done by sub-sampling GPS tracks recorded at 1-s sampling intervals, showing the effect that different sampling intervals have on metrics, including the total distance travelled and behavioural states derived from path length and turning angles. I show that for larger sampling intervals, the total distance travelled will be underestimated at varying degrees depending on flight sinuosity. By varying sampling rates when estimating behavioural states, I show that moderate (10–30 min) sampling intervals may produce better results. I explore the limitations of low-cost GPS loggers for fine-scale analyses and conclude that specialized loggers are most likely required when sampling at intervals < 1 s. In Chapter 4 I use specialized loggers in the form of tri-axial magnetometer, and video loggers and describe two novel methods to extract roll angles of albatrosses during dynamic soaring flight. Animal body angles are normally extracted by using tri-axial accelerometer data, but their dynamic soaring flight mode inhibits the use of these methods. I show how magnetometer data are independent of dynamic movement and can be used to estimate roll angles of flying seabirds. This method is validated from bird-borne video footage where the horizon is used as a proxy for the bird's roll angle and I describe a method to automatically extract such angles using computer vision techniques. These new methods are then applied to data collected from Wandering Albatrosses Diomedea exulans in Chapter 5, showing how the birds vary their roll angle in response to changing winds. Additionally, flapping flight was identified from patterns in the vertical axis (heave) of a tri-axial accelerometer and I show how Wandering Albatrosses may be flapping more than expected. By coupling flapping and roll angles I show that flapping, on occasion, occur at the upper turn of the dynamic soaring cycle, a period previous thought devoid of flaps. These results also suggest possible sexual differences, where males seem to flap more often than females and limit their take-offs to favourable wind conditions. Lastly, in Chapter 6 I use the same methods as in the previous two chapters to compare the fine-scale flight of six Procellariiformes species breeding on Marion, Gough and Nightingale Islands. I show how these species have varied flight patterns where they respond differently to wind patterns, most likely driving their distribution and eventual foraging areas. As expected, smaller species seem to be more manoeuvrable allowing them to rapidly roll at extreme angles in strong winds while tolerating light winds by increasing the amount of time spent flapping. Breeding location also played a role as birds from the Tristan da Cunha archipelago flapped more often and flew in lighter winds than Marion Island birds. In summary, Chapter 7 discusses how, using a multisensor approach, bio-logging technology can be effectively used to study the fine-scale behaviour of flying seabirds. Each of the loggers have their own limitations and it is important to take these into account when analyzing the data. I describe two new methods for extracting roll angles from dynamic soaring seabirds and show how individuals from several species vary roll angle and flapping flight in response to changing winds. This thesis highlights the varying behavioural strategies that flying seabirds use in the Southern Ocean, showing that individual species and populations may respond differently to changing environmental conditions

Circles within spirals, wheels within wheels; Body rotation facilitates critical insights into animal behavioural ecology

How animals behave is fundamental to enhancing their lifetime fitness, so defining how animals move in space and time relates to many ecological questions, including resource selection, activity budgets and animal movement networks. Historically, animal behaviour and movement has been defined by direct observation, however recent advancements in biotelemetry have revolutionised how we now assess behaviour, particularly allowing animals to be monitored when they cannot be seen. Studies now pair ‘convectional’ radio telemetries with motion sensors to facilitate more detailed investigations of animal space-use. Motion sensitive tags (containing e.g., accelerometers and magnetometers) provide precise data on body movements which characterise behaviour, and this has been exemplified in extensive studies using accelerometery data, which has been linked to space-use defined by GPS. Conversely, consideration of body rotation (particularly change in yaw) is virtually absent within the biologging literature, even though various scales of yaw rotation can reveal important patterns in behaviour and movement, with animal heading being a fundamental component characterising space-use. This thesis explores animal body angles, particularly about the yaw axis, for elucidating animal movement ecology. I used five model species (a reptile, a mammal and three birds) to demonstrate the value of assessing body rotation for investigating fine-scale movement-specific behaviours. As part of this, I advanced the ‘dead-reckoning’ method, where fine-scale animal movement between temporally poorly resolved GPS fixes can be deduced using heading vectors and speed. I addressed many issues with this protocol, highlighting errors and potential solutions but was able to show how this approach leads to insights into many difficult-to-study animal behaviours. These ranged from elucidating how and where lions cross supposedly impermeable man-made barriers to examining how penguins react to tidal currents and then navigate their way to their nests far from the sea in colonies enclosed within thick vegetation

Appalachia Winter/Spring 2022: Complete Issue

Winter/Spring 2022 - Volume LXXIII, Number 1 - Issue #253. Cataclysms in the Catskills and Taconics: Floods, Temperature Swings, and Bluebird

Informative soaring with drifting thermals

© 2016 IEEE. The informative soaring (IFS) problem involves a gliding unmanned aerial vehicle (UAV) exploiting energy from thermals to extend its information gathering capability. In this paper, we address the realistic situation of detecting new thermals drifting with the wind in the search environment. We consider complex target-search scenarios characterised by information clusters and propose a new set of algorithms designed to both explore for and exploit high-value thermals to maximise information gain. Our algorithms: 1) compute a thermal exploration map to detect useful thermals that eventually intercept clusters, 2) solve a boundary value problem for interthermal path segment (ITP) generation with moving thermals, 3) compute thermal time windows to gather information from clusters and form a cluster service schedule, and 4) use branch and bound (BnB) tree search for global planning, considering high-utility-rate ITPs to maximise information gain. Our solution is compared against a greedy method that neither considers the thermal exploration map nor cluster schedule and a full knowledge method that has access to all thermals. Numerical simulations show that on average, our solution outperforms the greedy method in one-third of 2400 Monte Carlo trials, and achieves similar performance to the full knowledge method when environmental conditions are favourable

Path planning algorithms for atmospheric science applications of autonomous aircraft systems

Among current techniques, used to assist the modelling of atmospheric processes, is an approach involving the balloon or aircraft launching of radiosondes, which travel along uncontrolled trajectories dependent on wind speed. Radiosondes are launched daily from numerous worldwide locations and the data collected is integral to numerical weather prediction.This thesis proposes an unmanned air system for atmospheric research, consisting of multiple, balloon-launched, autonomous gliders. The trajectories of the gliders are optimised for the uniform sampling of a volume of airspace and the efficient mapping of a particular physical or chemical measure. To accomplish this we have developed a series of algorithms for path planning, driven by the dual objectives of uncertainty andinformation gain.Algorithms for centralised, discrete path planning, a centralised, continuous planner and finally a decentralised, real-time, asynchronous planner are presented. The continuous heuristics search a look-up table of plausible manoeuvres generated by way of an offline flight dynamics model, ensuring that the optimised trajectories are flyable. Further to this, a greedy heuristic for path growth is introduced alongside a control for search coarseness, establishing a sliding control for the level of allowed global exploration, local exploitation and computational complexity. The algorithm is also integrated with a flight dynamics model, and communications and flight systems hardware, enabling software and hardware-in-the-loop simulations. The algorithm outperforms random search in two and three dimensions. We also assess the applicability of the unmanned air system in ‘real’ environments, accounting for the presence of complicated flow fields and boundaries. A case study based on the island South Georgia is presented and indicates good algorithm performance in strong, variable winds. We also examine the impact of co-operation within this multi-agent system of decentralised, unmanned gliders, investigating the threshold for communication range, which allows for optimal search whilst reducing both the cost of individual communication devices and the computational resources associated with the processing of data received by each aircraft. Reductions in communication radius are found to have a significant, negative impact upon the resulting efficiency of the system. To somewhat recover these losses, we utilise a sorting algorithm, determining information priority between any two aircraft in range. Furthermore, negotiation between aircraft is introduced, allowing aircraft to resolve any possible conflicts between selected paths, which helps to counteractany latency in the search heuristic