Effect of Communication Delays on the Successful Coordination of a Group of Biomimetic AUVs

In this paper, the influence of delays on the ability of a formation control algorithm to coordinate a group of twelve Biomimetic Autonomous Underwater Vehicles (BAUVs) is investigated. In this study the formation control algorithm is a decentralized methodology based on the behavioural mechanisms of fish within school structures. Incorporated within this algorithm is a representation of the well-known and frequently used communication protocol, Time-Division-Multiple-Access (TDMA). TDMA operates by assigning each vehicle a specific timeslot during which it can broadcast to the remaining members of the group. The size of this timeslot varies depending on a number of operational parameters such as the size of the message being transmitted, the hardware used and the distance between neighbouring vehicles. Therefore, in this work, numerous timeslot sizes are tested that range from theoretical possible values through to values used in practice. The formation control algorithm and the TDMA protocol have been implemented within a validated mathematical of the RoboSalmon BAUV designed and manufactured at the University of Glasgow. The results demonstrate a significant deterioration in the ability of the formation control algorithms as the timeslot size is increased. This deterioration is due to the fact that as the timeslot size is increased, the interim period between successive communication updates increases and as a result, the error between where the formation control algorithm estimates each vehicle to be and where they actually are, increases. As a result, since the algorithm no longer has an accurate representation of the positioning of neighbouring vehicles, it is no longer capable of selecting the correct behavioural equation and subsequently, is unable to coordinate the vehicles to form a stable group structure

Development of a formation control algorithm to coordinate multiple biomimetic AUVs in the presence of realistic environmental constraints

Biomimetic Autonomous Underwater Vehicles (BAUVs) are a class of Uncrewed Underwater Vehicle (UUV) that mimic the propulsive and steering mechanisms of real fish. However, as with all UUVs, the range and endurance of these vehicles remains limited by the finite energy source housed on board the vehicle. Unsurprisingly, a consequence of this finite energy source is that BAUVs/UUVs are incapable of completing the large-scale oceanographic sampling missions required to drastically improve our understanding of the Earth’s oceans and its processes. To overcome this limitation, this thesis aims to investigate the feasibility of deploying a self-coordinating group of BAUVs capable of completing the aforementioned oceanic surveying missions despite the constraints of the local operating environment. To achieve this, the work presented in this thesis can be separated into four distinct parts. The first of which is the development of a suitable mathematical model that accurately models the dynamics of the RoboSalmon BAUV designed and built at the University of Glasgow. As well as ensuring the models validity, its ability to efficiently simulate multiple vehicles simultaneously is also demonstrated. The design and implementation of the formation control algorithm used to coordinate the vehicles is then presented. This process describes the alterations made to a biologically-inspired algorithm to ensure the required parallel line formation required for efficient oceanic sampling can be generated. Thereafter, the implementation of a realistic representation of the underwater communication channel and its debilitating effect on the algorithms ability to coordinate the vehicles as required is presented. The thesis then describes the incorporation of two methodologies designed specifically to overcome the limitations associated with the underwater communication channel. The first of which involves the implementation of tracking/predictive functionality while the second is a consensus based algorithm that aims to reduce the algorithms reliance on the communication channel. The robustness of these two methodologies to overcoming not only the problematic communication channel but also the inclusion of additional external disturbances is then presented. The results demonstrate that while the tracking/predictive functionality can overcome the problems associated with the communication channel, its efficiency significantly reduces when the external disturbances are taken into consideration. The consensus based methodology meanwhile generates the required formation regardless of the constraints imposed by both the communication channel and the additional external disturbances and therefore provides the more robust solution

The Addenbrooke's Cognitive Examination for the differential diagnosis and longitudinal assessment of patients with parkinsonian disorders.

OBJECTIVE: Differentiating idiopathic Parkinson's disease from atypical parkinsonian syndromes is challenging, especially in the early stages. We assessed whether the Revised Addenbrooke's Cognitive Examination (ACE-R) could differentiate between parkinsonian syndromes and reflect longitudinal changes in cognition in these disorders. METHODS: The ACE-R was administered at baseline and after approximately 18 months to 135 patients with parkinsonian disorders: 86 with idiopathic Parkinson's disease (PD), 30 with progressive supranuclear palsy (PSP), 19 with corticobasal degeneration (CBD). We assessed differences between groups for ACE-R, ACE-R subscores and Mini Mental State Examination (MMSE) scores at baseline (analyses of variance, receiver operating characteristics curves), and the interaction between diagnosis and change in ACE-R scores between visits (analyses of variance). RESULTS: The ACE-R verbal fluency subscore distinguished between PSP and PD with a high sensitivity (0.92) and specificity (0.87); total ACE-R score and the visuospatial subscore were less specific (0.87 and 0.84 respectively) and sensitive (0.70 and 0.73). Significant group level differences were found between PD and PSP for MMSE and ACE-R (total score and subscores for attention and concentration, fluency, language, and visuospatial function), and between PD and CBD for the ACE-R visuospatial subscore. Performance worsened between visits for ACE-R score in PD (p=0.001) and CBD (p=0.001); visuospatial subscore in PD (p=0.003), PSP (p=0.022) and CBD (p=0.0002); and MMSE in CBD (p=0.004). CONCLUSIONS: We propose the ACE-R, particularly the verbal fluency subscore, as a valuable contributor to the differential diagnosis of parkinsonian syndromes in the correct clinical context. The ACE-R may reflect disease progression in PD and CBD

SteatoSITE: an Integrated Gene-to-Outcome Data Commons for Precision Medicine Research in NAFLD

Nonalcoholic fatty liver disease (NAFLD) is the commonest cause of chronic liver disease worldwide and a growing healthcare burden. The pathobiology of NAFLD is complex, disease progression is variable and unpredictable, and there are no qualified prognostic biomarkers or licensed pharmacotherapies that can improve clinical outcomes; it represents an unmet precision medicine challenge. We established a retrospective multicentre national cohort of 940 patients, across the complete NAFLD spectrum, integrating quantitative digital pathology, hepatic RNA-sequencing and 5.67 million days of longitudinal electronic health record follow-up into a secure, searchable, open resource (SteatoSITE) to inform rational biomarker and drug development and facilitate personalised medicine approaches for NAFLD. A complementary web-based gene browser was also developed. Here, our initial analysis uncovers disease stage-specific gene expression signatures, pathogenic hepatic cell subpopulations and master regulator networks associated with disease progression in NAFLD. Additionally, we construct novel transcriptional risk prediction tools for the development of future hepatic decompensation events

An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the commonest cause of chronic liver disease worldwide and represents an unmet precision medicine challenge. We established a retrospective national cohort of 940 histologically defined patients (55.4% men, 44.6% women; median body mass index 31.3; 32% with type 2 diabetes) covering the complete MASLD severity spectrum, and created a secure, searchable, open resource (SteatoSITE). In 668 cases and 39 controls, we generated hepatic bulk RNA sequencing data and performed differential gene expression and pathway analysis, including exploration of gender-specific differences. A web-based gene browser was also developed. We integrated histopathological assessments, transcriptomic data and 5.67 million days of time-stamped longitudinal electronic health record data to define disease-stage-specific gene expression signatures, pathogenic hepatic cell subpopulations and master regulator networks associated with adverse outcomes in MASLD. We constructed a 15-gene transcriptional risk score to predict future hepatic decompensation events (area under the receiver operating characteristic curve 0.86, 0.81 and 0.83 for 1-, 3- and 5-year risk, respectively). Additionally, thyroid hormone receptor beta regulon activity was identified as a critical suppressor of disease progression. SteatoSITE supports rational biomarker and drug development and facilitates precision medicine approaches for patients with MASLD

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Coordination of Multiple Biomimetic Autonomous Underwater Vehicles Using Strategies Based on the Schooling Behaviour of Fish

Biomimetic Autonomous Underwater Vehicles (BAUVs) are Autonomous Underwater Vehicles (AUVs) that employ similar propulsion and steering principles as real fish. While the real life applicability of these vehicles has yet to be fully investigated, laboratory investigations have demonstrated that at low speeds, the propulsive mechanism of these vehicles is more efficient when compared with propeller based AUVs. Furthermore, these vehicles have also demonstrated superior manoeuvrability characteristics when compared with conventional AUVs and Underwater Glider Systems (UGSs). Further performance benefits can be achieved through coordination of multiple BAUVs swimming in formation. In this study, the coordination strategy is based on the schooling behaviour of fish, which is a decentralized approach that allows multiple AUVs to be self-organizing. Such a strategy can be effectively utilized for large spatiotemporal data collection for oceanic monitoring and surveillance purposes. A validated mathematical model of the BAUV developed at the University of Glasgow, RoboSalmon, is used to represent the agents within a school formation. The performance of the coordination algorithm is assessed through simulation where system identification techniques are employed to improve simulation run time while ensuring accuracy is maintained. The simulation results demonstrate the effectiveness of implementing coordination algorithms based on the behavioural mechanisms of fish to allow a group of BAUVs to be considered self-organizing

Coordination of a School of Robotic Fish Using Nearest Neighbour Principles

Autonomous Underwater Vehicles (AUVs) are Unmanned Underwater Vehicles (UUVs) that are able to function without direct control from a human operator. Consequently, they have a wide range of applications from scientific research of the oceans to military applications such as maritime surveillance. However, there is now the demand for AUVs to be operated within a multi-vehicle scenario to allow large areas of the ocean to be monitored simultaneously. However, in order for this to become a reality algorithms have to be created that ensure that a group of AUVs could be self-organising. Therefore, using a validated mathematical model of a biomimetic robotic fish (called RoboSalmon) and taking inspiration from nature, this paper outlines the implementation of co-ordination algorithms based upon the behavioural mechanisms exhibited by schools of fish to allow a group of AUVs to become self-organising. The algorithms implemented are based on two different methodologies known as the Discrete and Continuous Behavioral Zone methodologies. The results obtained demonstrated that although both methodologies result in the formation of a school structure, the results obtained from the Continuous Behavioral Zone (CBZ) methodology were more resilient to changes in parameters associated with school structures and therefore these algorithms provided the most effective way to allow a group of AUVs to be considered as self-organising

Die k-Weierstrasspunktkonstellationen kompakter Riemannscher Flaechen

SIGLETIB: RO 1945 (77) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Analysis of the group structure of a school of biomimetic AUVS coordinated using nearest neighbour principles

Biomimetic Autonomous Underwater Vehicles are Autonomous Underwater Vehicles (AUVs) that employ similar propulsion and steering mechanisms as real fish which result in improvements in propulsive efficiency at low speed. However, as with all AUVs the range and endurance of these biologically inspired vehicles are severally limited by the on board power supply. Nevertheless, large area scanning can still be achieved by the coordinated movement of multiple vehicles. To allow this to happen co-ordination algorithms would have to be utilised to ensure that a group of AUVs would be self-organising. The particular methodology presented in this paper again takes inspiration from nature and is based upon the behavioural mechanisms exhibited by schools of fish. Therefore, using a validated mathematical model of a robotic fish (called RoboSalmon), this paper outlines the implementation of this algorithm which similarly to the behavioural mechanisms use nearest neighbor principles to determine the movement of each member of the group. As this paper will use a mathematical model of a biomimetic AUV to implement biologically inspired coordination algorithms, the resulting group structure will be analysed with reference to the formation of a group structure and the number of AUVs within a group that are in a position to take advantage of the hydrodynamic benefits known to exist from fish swimming in close formation. The results demonstrate that the number of nearest neighbours taking into consideration greatly affects the formation of a stable school structure whereas the size of the school dictates the number of AUVs within the group benefitting hydrodynamically from the close proximity of neighbouring fish