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

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

Inverse kinematics solution for trajectory tracking using artificial neural networks for SCORBOT ER-4u

This paper presents the kinematic analysis of the SCORBOT-ER 4u robot arm using a Multi-Layered Feed-Forward (MLFF) Neural Network. The SCORBOT-ER 4u is a 5-DOF vertical articulated educational robot with revolute joints. The Denavit-Hartenberg and Geometrical methods are the forward kinematic algorithms used to generate data and train the neural network. The learning of forward-inverse mapping enables the inverse kinematic solution to be found. The algorithm is tested on hardware (SCORBOT-ER 4u) and reliable results are obtained. The modeling and simulations are done using MATLAB 8.0 software

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

The design and implementation of a system for the automatic generation of narrative debriefs for AUV Missions

Increased autonomy allows autonomous underwater vehicles to act without direct support or supervision. This requires increased complexity, however, and a deficit of trust may form between operators and these complex machines, though previous research has shown this can be reduced through repeated experience with the system in question. Regardless of whether a mission is performed with real vehicles or their simulated counterparts, effective debrief represents the most efficient method for performing an analysis of the mission. A novel system is presented to maximise the effectiveness of a debrief by ordering the mission events using a narrative structure, which has been shown to be the quickest and most effective way of communicating information and building a situation model inside a person’s mind. Mission logs are de-constructed and analysed, then optimisation algorithms used to generate a coherent discourse based on the events of the missions with any required exposition. This is then combined with a timed mission playback and additional visual information to form an automated mission debrief. This approach was contrasted with two alternative techniques: a simpler chronological ordering; and a facsimile of the current state of the art. Results show that participant recall accuracy was higher and the need for redundant delivery of information was lower when compared to either of the baselines. Also apparent is a need for debriefs to be adapted to individual users and scenarios. Results are discussed in full, along with suggestions for future avenues of research

Swarm robotic systems: ypod formation with analysis on scalability and stability

Aquesta tesi se central en la formació d’eixams, on s’estudia el comportament coordinat d’un grup de robots per formar un patró quan s’observa a nivell global. En aquest sentit, la formació de la forma general és un dels problemes actuals en d’intel·ligència d’eixams artificials. En aquesta tesi s’introdueix una nova formació en forma de Y, la qual presenta una gran quantitat d’aplicacions en comparació amb altres tècniques de formació. Per exemple, la formació en Y es pot aplicar com a formació estratègica per totes les escales, presenta facilitat per canviar de forma i grandària a més de resoldre els problemes de redundància, d’autoorganització i autoreparació. L’objectiu principal d’aquesta tesi és aconseguir la formació en Y d’un eixam de robots. La implementació de dita formació únicament s’ha dut a terme mitjançant un entorn de simulació tot i que se han tingut en compte diferents aspectes que es podrien donar en una implementació real. El disseny del control de l’eixam per a diferents eixos s’ha realitzat a partir d’un model capaç de predir el comportament global de l’eixam, de la definició del temps d’establiment i l’aplicació de tècniques de localització de pols. Per controlar l’eixam en forma Y en termes d’orientació i el seu moviment com un bloc, s’han combinat el controlador lineal proposat, amb funcions límit i l’ajust d’alguns paràmetres per simulació. Els paràmetres s’han escollit per la formació desitjada i segons les constants definides per l’usuari. En comparació amb altres treballs, la solució proposta és simple, computacionalment eficient i tant per models d’eixams centralitzats com descentralitzats.Esta tesis se centra en la formación de enjambres, donde se estudia el comportamiento coordinado de un grupo de robots para formar un patrón cuando se observa a nivel global. En este sentido, la formación de la forma general es uno de los problemas actuales en la inteligencia de enjambres artificiales. En esta tesis se introduce una nueva formación en forma de Y, la cual presenta una gran cantidad de aplicaciones en comparación con otras técnicas de formación. Por ejemplo, la formación en Y se puede aplicar como formación estratégica para todas las escalas, presenta facilidad para cambiar de forma y tamaño además de resolver los problemas de redundancia, de auto-organización y auto-reparación. El objetivo principal de esta tesis es conseguir la formación en Y de un enjambre de robots. La implementación de dicha formación se ha llevado a cabo únicamente mediante un entorno de simulación aunque se han tenido en cuenta diferentes aspectos que se podrían dar en una implementación real. El diseño del control del enjambre para diferentes ejes se ha realizado a partir de un modelo capaz de predecir el comportamiento global del enjambre, de la definición del tiempo de establecimiento y la aplicación de técnicas de localización de polos. Para controlar el enjambre en forma de Y en términos de orientación y movimientos del enjambre como un bloque, se han combinado el controlador lineal propuesto, funciones límite y el ajuste de algunos parámetros por simulación. Los parámetros se han escogido para la formación deseada y según las constantes definidas por el usuario. En comparación con otros trabajos, la solución propuesta es simple, computacionalmente eficiente, y tanto para modelos de enjambres centralizados como descentralizados.The context of this work is the innovative young filed of swarm robotics. Particularly, in this thesis focused on swarm formation, which is important in swarm robotics too since coordinated behaviour of a group of robots to form a pattern when viewed globally. In this regard, global shape formation is one of the ongoing problems in artificial swarm intelligence. In nature, it is performed for various purposes, and search and rescue swarms could be used in disaster areas .In robotics phenomena, there exist various shape formations in the literature, but in this thesis, introduced new shape formation Y-Pod, which has vast applications compare to other formation techniques. In the discussion of our research journey, me and my supervisor discussed about various shape formations but finally exploit new shape formation Y-Pod and when we think about it, arise some questions ,why Y-Pod swarm formation and what it will serve, so in our casual discussion some important advantages are identified, those are : The Y-Pod can be utilized for formation strategy on all scales, Global shape formation, when viewed globally, Changes shapes, Easy to expand, overcome the redundancy problems and Self-organized and self-repair problems. The main objective of the proposed approach is to form a Y-pod formation of swarm robots. As well as we keep in our mind for real robot performance task, but the original work is delivered in simulation based environment only. Several parameters that significantly define the resulting behavior. We have proposed system equilibrium parameters with settling time and pole based problems, to control the swarm system in various axis an accurate model will predict the global behavior of the Y-Pod swarm formation based on the mathematical identified parameters. The proposed linear controller, limiting functions and simulation tuned parameters are combined to control Y-Pod swarm formation in terms of orientation, and swarm movement as a whole. Parameters are chosen based on desired formation as well as user defined constraints. This approach compared to others, is simple, computationally efficient, scales well to different swarm sizes, to heterogeneous systems, and to both centralized and decentralized swarm models

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics

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

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described