Chaotic exploration and learning of locomotion behaviours

We present a general and fully dynamic neural system, which exploits intrinsic chaotic dynamics, for the real-time goal-directed exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modeled as a network of neural oscillators that are initially coupled only through physical embodiment, and goal-directed exploration of coordinated motor patterns is achieved by chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organized dynamics, each of which is a candidate for a locomotion behavior. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states, using its intrinsic chaotic dynamics as a driving force, and stabilizes on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced, which results in an increased diversity of motor outputs, thus achieving multiscale exploration. A rhythmic pattern discovered by this process is memorized and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronization method. Our results show that the novel neurorobotic system is able to create and learn multiple locomotion behaviors for a wide range of body configurations and physical environments and can readapt in realtime after sustaining damage

Digital control networks for virtual creatures

Robot control systems evolved with genetic algorithms traditionally take the form of floating-point neural network models. This thesis proposes that digital control systems, such as quantised neural networks and logical networks, may also be used for the task of robot control. The inspiration for this is the observation that the dynamics of discrete networks may contain cyclic attractors which generate rhythmic behaviour, and that rhythmic behaviour underlies the central pattern generators which drive lowlevel motor activity in the biological world. To investigate this a series of experiments were carried out in a simulated physically realistic 3D world. The performance of evolved controllers was evaluated on two well known control tasks—pole balancing, and locomotion of evolved morphologies. The performance of evolved digital controllers was compared to evolved floating-point neural networks. The results show that the digital implementations are competitive with floating-point designs on both of the benchmark problems. In addition, the first reported evolution from scratch of a biped walker is presented, demonstrating that when all parameters are left open to evolutionary optimisation complex behaviour can result from simple components

The House of Feathers: a design practice observed, documented and represented

This invitational PhD by Project is an exploration and examination of the way in which I practice and how this informs what I know about my atelier, Studiobird. The invitation was an opportunity to enquire after my practice methodologies through the observation, documentation and representation of the projects conceived and developed within my atelier. As an invited candidate I have produced this document as a comprehensive account of how my practice has mastered a particular way of doing and thinking and how this thinking and doing could be framed and focused by the contemplative lens availed by the undertaking of a PhD. This document illustrates my projects, practice associations and practice methodologies from the position of a ‘practitioner’. Through this PhD undertaking I have exposed my architectural practice by way of presenting my liminal research findings as a ritualistic assemblage termed as ‘The House of Feathers’. The liminal research encompassed the extremes of conventional and non-conventional architecture. This assemblage is the embodiment of my practice knowledge, practice methodologies and by way of this PhD, practice revelations. The House of Feathers is further mediated by The House of Feathers Interactive Platform, constructed as a digital tool with which to navigate the principles of composition that designate the surfacing of my practice. This PhD accounts for the ways in which my thinking and doing constitute the conditions by which I define my practice. I offer both analytical and situated methods of enquiry in the form of a documentation of my practice outcomes and the Interactive Platform as both artefact of the enactment of this practice as ways by which I demonstrate the originality of my practice. This PhD, The House of Feathers addresses the explicit and complex entanglement of thinking and doing that manifest themselves within a design practice and how this approach may be tailored to envisage the future of such practices

INVESTIGATING DORSAL FIN HYDRODYNAMIC FUNCTION OF THE LEMON SHARK, NEGAPRION BREVIROSTRIS

Many sharks are considered highly efficient swimmers. Their swimming efficiency is partially governed by their morphological features such as dorsal fins, which play a role in their hydrodynamics. Most sharks feature two dorsal fins that can vary in size and location over the body. The first dorsal fin has been shown to improve stabilization, maneuverability, and increase thrust production during swimming, whilst the hydrodynamic role of the second dorsal fin is largely unknown. An understanding of the hydrodynamic function of the dorsal fins can be utilized in engineering applications, e.g., to replicate fins on underwater autonomous vehicles to increase energy efficiency during locomotion. To explore the hydrodynamics of the second dorsal fin and seek solutions applicable to the biomimetic world, we selected a species with a second dorsal fin that is almost as large as its first dorsal fin: the Lemon Shark. An enlarged second dorsal fin is an uncommon characteristic among sharks. Here, we performed a comparative study between the Lemon Shark and another shark species that has a small 2nd dorsal fin compared to the first: the Spinner Shark. We experimentally investigated the hydrodynamic role of the 2nd dorsal fin of the Lemon Shark and used particle image velocimetry to measure the fluid dynamics in its wake. Measurements were collected in the streamwise-spanwise plane behind the 1st and 2nd dorsal fins, as well as the caudal fin for deceased sharks of both species (Spinner Shark and Lemon Shark). In addition, a 3D flexible Lemon Shark model was also used to compare with the deceased specimens. Using the measured data, we: i) evaluated the characteristics of the specimens\u27 and model\u27s wake and ii) examined what effect these characteristics have on the hydrodynamic forces acting on the sharks. The presence of a vortex street in the wake was identified using proper orthogonal decomposition (POD). Based on the POD, the vortex street characteristics such as: wavelength, cross-stream distance, spacing ratio, Kronauer stability, von-Karman stability, and Strouhal number were computed. These wake characteristics were used to compute the thrust, and the drag was computed based on the momentum deficit in the wake. Results showed a stable vortex street developed in the wake behind the 1st dorsal fin for both species. Although the Lemon Shark had two dorsal fins similar in size, the Lemon Shark\u27s 2nd dorsal fin did not feature a vortex street in the wake. The size of the wake was larger than that of the 1st dorsal fin, which resulted in higher drag behind the second dorsal fin compared to the first dorsal fin. It was also found that the flow behind the 2nd dorsal fin did not fully recover prior to reaching the caudal fin, which indicated some interaction with the wake formation behind the caudal fin. It appeared that this interaction reduced the size of the overall wake for the Lemon Shark. Ultimately, this smaller wake resulted in lower drag behind the caudal fin compared to a species with only one large dorsal fin, like the Spinner Shark

Evolutionary robotics in high altitude wind energy applications

Recent years have seen the development of wind energy conversion systems that can exploit the superior wind resource that exists at altitudes above current wind turbine technology. One class of these systems incorporates a flying wing tethered to the ground which drives a winch at ground level. The wings often resemble sports kites, being composed of a combination of fabric and stiffening elements. Such wings are subject to load dependent deformation which makes them particularly difficult to model and control. Here we apply the techniques of evolutionary robotics i.e. evolution of neural network controllers using genetic algorithms, to the task of controlling a steerable kite. We introduce a multibody kite simulation that is used in an evolutionary process in which the kite is subject to deformation. We demonstrate how discrete time recurrent neural networks that are evolved to maximise line tension fly the kite in repeated looping trajectories similar to those seen using other methods. We show that these controllers are robust to limited environmental variation but show poor generalisation and occasional failure even after extended evolution. We show that continuous time recurrent neural networks (CTRNNs) can be evolved that are capable of flying appropriate repeated trajectories even when the length of the flying lines are changing. We also show that CTRNNs can be evolved that stabilise kites with a wide range of physical attributes at a given position in the sky, and systematically add noise to the simulated task in order to maximise the transferability of the behaviour to a real world system. We demonstrate how the difficulty of the task must be increased during the evolutionary process to deal with this extreme variability in small increments. We describe the development of a real world testing platform on which the evolved neurocontrollers can be tested

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

Fluid Mechanics of Plankton

The cooperation between plankton biologists and fluid dynamists has enhanced our knowledge of life within the plankton communities in ponds, lakes, and seas. This book assembled contributions on plankton–flow interactions, with an emphasis on syntheses and/or predictions. However, a wide range of novel insights, reasonable scenarios, and founded critiques are also considered in this book

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties