Expressive Swarms: towards building better human-swarm communication

Project description:
Swarm robotic systems aim to produce collective behaviour through self-organised and decentralised mechanisms of control. The agents in this system depend on local interactions among one another, and interactions with the environment, to make decisions. If one agent fails, the rest of the system continues to function. Therefore, swarm robotic systems aim to be robust, scalable and flexible. The complexity of self-organised, decentralised control means that ordinarily these systems are created with a very high degree of autonomy.

Such systems contain large number of agents, which produces a challenge when human interaction is introduced to the system. It is not feasible for the human to control each and every agent in the system due to their large number. Additionally, the task of integrating human interaction into the robotic system becomes more challenging because it interferes with the mechanisms of self-organisation. However, when a swarm robotic system is applied to a problem or a task, it would be useful to be able to steer, influence or understand the system. Hence, the field of human-swarm interaction (HSI) arose. In HSI, the aim is to give the human the ability to influence the swarm system as a whole, as opposed to controlling each individual robot, or imposing a centralised control scheme.

Swarm systems may not behave perfectly, and they experience failure modes. Similarly, a human might perform errors during interaction, especially with increased numbers of agents. Hence, to reach a balance, human-swarm interaction must provide a human with a method of influencing the swarm behaviour as a whole, and at the same time, preserve the autonomy and self-organisation of the system. Striking this balance effectively is the core of the research domain.

A key parameter of human-swarm interaction is the mutual understanding of the state of the interaction between the human and the swarm. Just as it is crucial to ensure that the swarm system understands the human's interaction, it is also crucial that the human understands the state of the swarm in order to determine whether their interaction took effect, and what action to take to assert their influence. Therefore, the idea of "Expressive Swarms" in this project aims at creating a swarm system that communicates its state in an expressive manner that is easily readable by a human operator. Since creating expressive swarms has the potential of easing the human-swarm interaction task, different real-world scenarios will be studied and deployed during the work of this project, where expressing the state of the system is crucial. The research will necessitate measures of interactivity and expressivity, and whether these were congruous with the task/performance of the swarm.

This project contributes to the area of human-swarm interaction by developing a swarm system that is decentralised yet allows a human to effectively interact with it without breaking its decentralisation. Furthermore, the contribution of this project is to break new ground on measures and quantifiable human-swarm interaction.

The project will develop a number of human-swarm interaction modes that enable the human to interact successfully with the robots. Those modes will each create a feedback (such as visualisation) which expresses the internal state of the swarm system as a whole. These modes will be experimentally investigated for their effectiveness in communication, as well as the effects of the human interaction on the swarming performance. All the interaction modes will be developed within the core constraints of a swarm robotic system - the autonomy and decentralisation of the swarm will be preserved. In other words, the robots will use local interactions among one another, and interaction with their environment around them, in order to make a decision on what type of human interaction took place, if any, and consequently provide an expressive feedback.

FARSCOPE-TU will deliver a step change in UK capabilities in robotics and autonomous systems (RAS) by elevating technologies from niche to ubiquity. It meets the critical need for advanced RAS, placing the UK in prime position to capture a significant proportion of the estimated $18bn global market in advanced service robotics. FARSCOPE-TU will provide an advanced training network in RAS, pump priming a generation of professional and adaptable engineers and leaders who can integrate fundamental and applied innovation, thereby making impact across all the "four nations" in EPSRC's Delivery Plan. Specifically, it will have significant immediate and ongoing impact in the following six areas:
1. Training: The FARSCOPE-TU coherent strategy will deliver five cohorts trained in state-of-the-art RAS research, enterprise, responsible innovation and communication. Our students will be trained with wide knowledge of all robotics, and deep specialist skills in core domains, all within the context of the 'innovation pipeline', meeting the need for 'can-do' research engineers, unafraid to tackle new and emergent technical challenges. Students will graduate as future thought leaders, ready for deployment across UK research and industrial innovation.
2. Partner and industrial impact: The FARSCOPE-TU programme has been designed in collaboration with our industrial and end-user partners, including: DSTL; Thales; Atkins; Toshiba; Roke Manor Research; Network Rail; BT; National Nuclear Lab; AECOM; RNTNE Hospital; Designability; Bristol Heart Inst.; FiveAI; Ordnance Survey; TVS; Shadow Robot Co.; React AI; RACE (part of UKAEA) and Aimsun. Partners will deliver context and application-oriented training direct to the students throughout the course, ensuring graduates are perfectly placed to transition into their businesses and deliver rapid impact.
3. RAS community: FARSCOPE-TU will act as multidisciplinary centre in robotics and autonomous systems for the whole RAS community, provide an inclusive model for future research and training centres and bring new opportunities for networking between other centres. These include joint annual conference with other RAS CDTs and training exchanges. FARSCOPE-TU will generate significant international exposure within and beyond the RAS community, including major robotics events such as ICRA and IROS, and will interface directly with the UK-RAS network.
4. Societal Impact: FARSCOPE-TU will promote an informed debate on the adoption of autonomous robotics in society, cutting through hype and fear while promoting the highest levels of ethics and safety. All students will design and deliver public engagement events to schools and the public, generating knock-on impact in two ways: greater STEM uptake enhances future economic potential, and greater awareness makes people better users of robots, amplifying societal benefits.
5. Economic impact: FARSCOPE-TU will not only train cohorts in fundamental and applied research but will also demonstrate how to bridge the "technology valley of death" between lower and higher TRL. This will enable students to exploit their ideas in technology incubators (incl. BRL incubator, SetSquared and EngineShed) and through IP protection. FARSCOPE-TU's vision of ubiquitous robotics will extend its impact across all UK industrial and social sectors, from energy suppliers, transport and agriculture to healthcare, aging and human-machine interaction. It will pump-prime ubiquitous UK robotics, inspiring and enabling myriad new businesses and economic and social impact opportunities.
6. Long-term Impact: FARSCOPE-TU will have long-term impact beyond the funded lifetime of the Centre through a network for alumni, enabling knowledge exchange and networking between current and past students, and with partners and research groups. FARSCOPE-TU will have significant positive impact on the 80-strong non-CDT postgraduate student body in BRL, extending best-practice in supervision and training.