Outdoor Stochastic Swarm for environmental monitoring

Searching or in-situ monitoring of an area require methods of covering the area with a large number of ground-based sensing units. In circumstances which prevent manual placement or units being dropped from the air these units must also deploy themselves into the environment from a small number of deployment points. The majority of literature regarding deploying large numbers of robots in an unknown environment considers virtual force approaches. However, in simulations carried out during a dissertation module an impressive coverage performance, in terms of speed and area, could be achieved by a large swarm using random walk strategy similar to that in [1]. Random walk approaches for the deployment problem have been investigated in complex indoor environments using simulation [1,2] and in open planar environments using swarm robotic hardware [3,4]. However, the potential benefits for random walk's use in ground based outdoor environments is yet to be explored.
While the random walking technique requires large numbers of robots to be produced, this could be feasible given that the required complexity of the individual robots, in terms of sensing and computation, is quite low. There is also the potential for random walking behaviour to be generated by each robot's hardware (e.g. introduced during rapid prototyping fabrication) rather than its microcontroller, which could reduce cost and improve scalability of manufacture. To use random walk approaches in the outdoor ground environment requires a swarm robotic platform that is streamlined for both performing random walk algorithms and overcoming rugged terrain. This project aims investigate the characteristics of random walking deployment of a homogeneous swarm in an outdoor environment by building such a platform. The project will first aim to understand the characteristics that make a successful swarm of random walkers (a stochastic swarm), then develop an individual robot which will exhibit these and finally create a full swarm for an outdoor experiment.
Random walk simulations
Random walking algorithms [1,5,6] cause robots to move in a stochastic manner by choosing their movement direction at random and reacting (or not) to obstacles they encounter. These methods have been presented as methods for exploring or searching unknown environments when sensory cues are unavailable, or map-based techniques are beyond the robot's abilities [4]. In swarm robotics they have both been used as searching [6] and deployment strategies [1,7]. However, most studies do not consider the locomotion mechanism of the agent which could provide many different modalities of movement and levels of motion noise due its interaction with the environment. The first part of this project would aim to develop a theoretical understanding of random walking algorithms in the context of a swarm of robots. These simulations would explore the parameter space of random walker design. They would aim to explore the relative sizes of the robots to their environment, characteristics of the robot's locomotion and the effectiveness of various random walk algorithms. The simulations would also explore the guarantees around the connectivity of inter-robot communication and swarm requirements such as the number of robots required for a given area.
Stochastic Swarm hardware development
At small scales, outdoor terrain which appears relatively smooth to humans can become a challenging obstacle to small robotic agents due their size. This challenge has been tackled in robotics with many studies designing hopping mechanisms [8], legged robots [9] and whegs [10]. Each of these gives a variety of locomotion modalities with various trade-offs in energy consumption and speed. However, few studies have looked at the simultaneous design of locomotion methods alongside random walk algorithms. It therefore may be possible to develop a locomotion mechanism that is optimised for generating random walk motion while allowing t

Rapid growth in the already burgeoning Robotics and Autonomous Systems (RAS) market has been estimated from many sources. This growth is driven by socio-economic needs and enabled by advances in algorithms and technologies converging on robotics. The market potential for applications of robotics and autonomous systems is, therefore, of huge value to the UK. There are four major areas where FARSCOPE will strive to fulfil and deliver on the impact agenda.

1. Training: A coherent strategy for impact must observe the value of the 'innovation pipeline'; from training of world-class researchers to novel products in the 'shop window'. The FARSCOPE training programme described in the Case for Support will produce researchers who will be able to advance knowledge, expertise and skills in the many associated aspects of academic pursuit in the field. Crucially, they will be guided by its industrial partners and BRL's Industrial Advisory Group, so that they are grounded in the real-world context of the many robotics and autonomous systems application domains. This means pursuing research excellence while embracing the challenges set within the context of a range of real-world factors.

2. Economic and Social Exploitation: The elevated position of advanced robotics, in the commercial 'value chain', makes it imperative that we create graduates from our Centre who are acutely aware of this potential. BRL is centrally engaged in its regional SME and business ecology, as evidenced by its recent industry workshop and 'open lab' events, which attracted some 60 and 280 industrial delegates respectively. BRL is also a key contributor to regional economic innovation. BRL has engaged two business managers and allocated some dedicated space to specifically support work on RAS related industrial engagement and innovation and, importantly, technology incubation. BRL will be creating an EU-funded Robotics Innovation Facilities to help coordinating a EUR 20m a programme to specifically promote and encourage direct links between academia and industry with a focus on SMEs. All of these high-impact BRL activities will be fed directly into the FARSCOPE programme.

A critical mass of key industrial and end-user partnerships across a diverse array of sectors have given their support to the FARSCOPE centre. All have indicated their interest in engaging through the FARSCOPE mechanisms identified in the Case for Support. These demonstrate the impact of the FARSCOPE centre in engaging existing, and forming new, strategic partnerships in the RAS field.

3. Fostering links with other Research Institutions and Academic Dissemination: It is essential that FARSCOPE CDT students learn to share best practice with other RAS research centres, both in the UK and beyond. In addition to attendance and presentation at academic conferences nationally and overseas, FARSCOPE will use the following mechanisms to engage with the academic community. BRL has very many strong links with the UK, EU and global RAS research community. We will use these as a basis for cementing existing links and fostering new ones.

4. Engaging the Public: FARSCOPE will train and then encourage its student cohorts to engage with the general public, to educate about the potential of these new technologies, to participate in debates on ethics, safety and legality of autonomous systems, and to enthuse future generations to work in this exciting area. UWE and the University of Bristol, BRL's two supporting institutions, host the National Coordinating Centre for Public Engagement. In addition, UWE's Science Communication Unit is internationally renowned for its diverse and innovative activities, which engage the public with science. FARSCOPE students will receive guidance and training in public engagement in order to act as worthy RAS research 'ambassadors'.