898 research outputs found

    A fractally fractionated spacecraft

    Get PDF
    The advantages of decentralised multi-spacecraft architectures for many space applications are well understood. Distributed antennas represent popularly envisaged applications of such an architecture; these are composed of, typically, receiving elements carried on-board multiple spacecraft in precise formation. In this paper decentralised control, based on artificial potential functions, together with a fractal-like connection network, is used to produce autonomous and verifiable deployment and formation control of a swarm of spacecraft into a fractal-like pattern. The effect of using fractal-like routing of control data within the spacecraft generates complex formation shape patterns, while simultaneously reducing the amount of control information required to form such complex formation shapes. Furthermore, the techniques used ensures against swarm fragmentation, which can otherwise be a consequence of the non-uniform connectivity of the communication graph. In particular, the superposition of potential functions operating at multiple levels (single agents, subgroups of agents, groups of agents) according to a self-similar adjacency matrix produces a fractal-like final deployment with the same stability property on each scale. Results from the investigations carried out indicate the approach is feasible, whilst outlining its robustness characteristics, and versatility in formation deployment and control. Considering future high-precision formation flying and control capabilities, this paper considers, for the first time and as an example of a fractally fractionated spacecraft, a decentralised multi-spacecraft fractal shaped antenna. Furthermore, multi-spacecraft architecture exploiting fractal-like formations can be considered to investigate multi-scale phenomena in areas such as cosmic radiation and space plasma physics. Both numerical simulations and analytic treatment are presented, demonstrating the feasibility of deploying and controlling a fractionated fractal antenna in space through autonomous decentralised means. This work frames the problem of architecture and tackles the one of control, whilst not neglecting actuation

    Swarm shape manipulation through connection control

    Get PDF
    The control of a large swarm of distributed agents is a well known challenge within the study of unmanned autonomous systems. However, it also presents many new opportunities. The advantages of operating a swarm through distributed means has been assessed in the literature for efficiency from both operational and economical aspects; practically as the number of agents increases, distributed control is favoured over centralised control, as it can reduce agent computational costs and increase robustness on the swarm. Distributed architectures, however, can present the drawback of requiring knowledge of the whole swarm state, therefore limiting the scalability of the swarm. In this paper a strategy is presented to address the challenges of distributed architectures, changing the way in which the swarm shape is controlled and providing a step towards verifiable swarm behaviour, achieving new configurations, while saving communication and computation resources. Instead of applying change at agent level (e.g. modify its guidance law), the sensing of the agents is addressed to a portion of agents, differentially driving their behaviour. This strategy is applied for swarms controlled by artificial potential functions which would ordinarily require global knowledge and all-to-all interactions. Limiting the agents' knowledge is proposed for the first time in this work as a methodology rather than obstacle to obtain desired swarm behaviour

    Fractal patterns in fractionated spacecraft

    Get PDF
    Multi spacecraft architectures have been addressed in response to the demand for flexible architectures with high reliability and reduced costs compared to traditional monolithic spacecraft. A task that can be easily carried out by this kind of systems is the deployment of distributed antennas; these are composed of, typically, receiving elements carried on-board multiple spacecraft in precise formation. In this paper decentralised control means, based on artificial potential functions, together with a fractal-like connection network, are used to produce the autonomous and verifiable deployment and formation control of a swarm of spacecraft into a fractal-like pattern. The effect of using fractal-like routing of control data within the spacecraft generates complex formation shape patterns, while simultaneously reducing the amount of control information required to form such complex formation shapes. Furthermore, the techniques used ensure against swarm fragmentation, while exploiting communication channels anyway needed in a fractionated architecture. In particular, the superposition of potential functions operating at multiple levels (single agents, subgroups of agents, groups of agents) according to a self-similar adjacency matrix produces a fractal-like final deployment with the same stability property on each scale. Considering future high-precision formation flying and control capabilities, this paper considers, for the first time and as an example of a fractionated spacecraft, a decentralised multi-spacecraft fractal shaped antenna. A fractal antenna pattern provides multiple resonance peaks, directly related to the ratios of its characteristic physical lengths. Such a scenario would significantly improve the level of functionality of any multi-spacecraft synthetic aperture antenna system. Furthermore, multi-spacecraft architecture exploiting particular inter agent spacing can be considered to investigate multi-scale phenomena in areas such as cosmic radiation and space plasma physics. Both numerical simulations and analytic treatment are carried out demonstrating the feasibility of deploying and controlling a fractionated fractal antenna in space through autonomous decentralised means

    Contextually Aware Intelligent Control Agents for Heterogeneous Swarms

    Full text link
    An emerging challenge in swarm shepherding research is to design effective and efficient artificial intelligence algorithms that maintain a low-computational ceiling while increasing the swarm's abilities to operate in diverse contexts. We propose a methodology to design a context-aware swarm-control intelligent agent. The intelligent control agent (shepherd) first uses swarm metrics to recognise the type of swarm it interacts with to then select a suitable parameterisation from its behavioural library for that particular swarm type. The design principle of our methodology is to increase the situation awareness (i.e. information contents) of the control agent without sacrificing the low-computational cost necessary for efficient swarm control. We demonstrate successful shepherding in both homogeneous and heterogeneous swarms.Comment: 37 pages, 3 figures, 11 table

    Quality-sensitive foraging by a robot swarm through virtual pheromone trails

    Get PDF
    Large swarms of simple autonomous robots can be employed to find objects clustered at random locations, and transport them to a central depot. This solution offers system parallelisation through concurrent environment exploration and object collection by several robots, but it also introduces the challenge of robot coordination. Inspired by ants’ foraging behaviour, we successfully tackle robot swarm coordination through indirect stigmergic communication in the form of virtual pheromone trails. We design and implement a robot swarm composed of up to 100 Kilobots using the recent technology Augmented Reality for Kilobots (ARK). Using pheromone trails, our memoryless robots rediscover object sources that have been located previously. The emerging collective dynamics show a throughput inversely proportional to the source distance. We assume environments with multiple sources, each providing objects of different qualities, and we investigate how the robot swarm balances the quality-distance trade-off by using quality-sensitive pheromone trails. To our knowledge this work represents the largest robotic experiment in stigmergic foraging, and is the first complete demonstration of ARK, showcasing the set of unique functionalities it provides

    The impact of agent density on scalability in collective systems : noise-induced versus majority-based bistability

    Get PDF
    In this paper, we show that non-uniform distributions in swarms of agents have an impact on the scalability of collective decision-making. In particular, we highlight the relevance of noise-induced bistability in very sparse swarm systems and the failure of these systems to scale. Our work is based on three decision models. In the first model, each agent can change its decision after being recruited by a nearby agent. The second model captures the dynamics of dense swarms controlled by the majority rule (i.e., agents switch their opinion to comply with that of the majority of their neighbors). The third model combines the first two, with the aim of studying the role of non-uniform swarm density in the performance of collective decision-making. Based on the three models, we formulate a set of requirements for convergence and scalability in collective decision-making
    corecore