YorRobots Exhibition

Computer Science Building, Campus East, University of York

Robotics and AI have the potential to achieve significant benefits in applications in extreme environments including nuclear decommissioning, waste processing, and nuclear fusion inspection and maintenance. Benefits can include improvements to human safety, quality of working conditions, reduced cognitive load, reduced timescales and costs, and environmental remediation.

For the nuclear industry, and other high-consequence industries to enjoy the potential benefits of robotics and AI, people will need to be convinced that these systems are safe, secure and reliable. This talk will explore some of the common challenges in deploying robotics and AI in extreme environments, as well as highlighting some of the benefits. Examples from the nuclear industry will be given.

Robotics and Autonomous Systems are being developed all over the world, at an ever increasing pace. To benefit from these advances, we need to be confident that they are safe, and this is a complex issue. The University of York is a world-leader in the disciplines that contribute to understanding and demonstrating the safety of RAS, and together we are answering basic research questions and applying our knowledge to industry problems. Two key schemes are the Assuring Autonomy International Programme, focussing on safety assurance and regulation, and the Institute for Safe Autonomy, a £35M pioneering research initiative.

We will present lessons learnt from autonomous system development, focused on the on-going research being conducted by Thales in the areas of human factors and systems engineering. We provide information arising from past incident investigations and future academic research planned as part of the Thales Research and Development activities.

Driving is inherently social. When sharing the road, we constantly and rapidly predict the behaviour of the people and vehicles around us, signal our own intentions, and coordinate with others. Safety depends upon these social cognitive processes, but we know remarkably little about how they function on the road. The advent of autonomous vehicles brings this ignorance into sharp focus, raising important questions. When, if ever, do people engage their automatic social cognitive mechanisms in predicting autonomous vehicle behaviour? How can people communicate and coordinate with autonomous vehicles in a seamless fashion? And how can automotive design capitalize on the inherently social nature of the brain to design automobiles that interact smoothly and naturally with people (inside or outside the vehicle)? Here at the University of York, we have been developing a “social driving simulator” to help address these questions and to explore new lines of research at the intersection of psychology and robotics.

Robots are increasingly changing how we work and play, but the way software is developed to control these machines is costly because it involves so much trial and error. The RoboStar research group (at York, Sheffield, Leicester, France, and Brazil) is designing a model-based approach for validation, verification, and automatic generation of code and tests. The mathematical underpinning of the techniques provides confidence in the results. The goal is to enable development of control software for better quality robotics at a lower cost.

Robotics is changing the landscape of innovation. But traditional design approaches are not suited to novel or unknown habitats and contexts, for instance: robot colonies for ore mining, exploring or developing other planets or asteroids, or robot swarms for monitoring extreme environments on Earth. New design methodologies are needed that support optimising robot behaviour under different conditions for different purposes. It is accepted that behaviour is determined by a combination of the body (morphology, hardware) and the mind (controller, software). Embodied AI and morphological computing have made major progress in engineering artificial agents (i.e., robots) by focusing on the links between morphology and intelligence of natural agents (i.e., animals). While such a holistic body-mind approach has been hailed for its merits, we still lack an actual pathway to achieve this. This talk will consider the ARE project which focuses on a disruptive robotic technology where robots are created, reproduce and evolve in real-time and real space. The long-term vision is a technology enabling the evolution of entire autonomous robotic ecosystems that live and work for long periods in challenging and dynamic environments without the need for direct human oversight.

Long term service agreements have put the emphasis of maintenance and repair of engines on to OEM’s. To minimise customer disruption, Rolls-Royce provides as much corrective action whilst the engine is still installed as possible. Rolls-Royce, together with a set of strategic collaborators, is embarking on a wide range of ambitious programmes with which to expand on the portfolio of available services. This presentation aims to illustrate the strategic intentions of Rolls-Royce, and show a small selection of projects at a assortment of maturities.

Giving robots a sense of touch is vital to having them effectively perform risky tasks that currently only humans can do. In this talk, Rich Walker, Managing Director at the Shadow Robot Company, will explain the current challenges and opportunities for sending robots into extreme environments and give some insights into future research challenges.

Scientists are dependent on lead chemical compounds with precise ‘drugable’ properties. Chemical synthesis of a new drug target often requires many reaction steps. A key problem is in optimising each chemical reaction, which is a labour-intensive and time-consuming process. It is common to dedicate six months to one reaction step, creating a drug development bottleneck, arising from the way that chemical reactions are optimised. This inefficient work pattern operates in chemical synthesis laboratories the world over. Using a combination of robotics, statistical analysis and machine learning it is possible to greatly improve the chemical synthesis of drug targets. I will introduce new approaches used in our research programmes in my talk. Improving reaction efficiency, sustainability and safety are key drivers for the use of robotic systems in chemical synthesis.

Climate change, the greatest known environmental threat of the 21st century, requires long-term solutions to reduce the emission of Greenhouse Gases (GHGs) and more activities which remove GHGs from the atmosphere. Regular discussion of the importance of carbon uptake of trees masks the complexity of the situation: a complex pathway for carbon to flow into unseen soil ecosystems in potentially long-term stores. Unfortunately, nearly half of this valuable store is quickly lost back from the soil to the atmosphere due to unwitting land management choices.

Autonomous field-deployable technologies, which are needed by researchers and ultimately by policy makers with an interest in reducing overall terrestrial emissions, have been developed at York through a series of research projects. One output, the SkyLine2D system, is a robust, highly resolved solution to the non-trivial problem of autonomously locating and sealing a measurement chamber over vegetation and soil to continuously measure GHG emission and uptake in real-world conditions. 

Collaboration between engineers and field scientists have produced a system which is now in use in a range of studies to assess the impact of factors such as: fertiliser addition, watering regime, crop type, pharmaceutical pollution, and future increases in temperature and atmospheric CO2; revealing this unseen part of the carbon cycle.

Over the 20+ years Dyson has been working on domestic robots the challenges of developing a mass market product have evolved. In this talk we will outline how the increasing environment optimisation, user needs, technology complexity and cost of development have driven changes to how we predict, measure, assure and test the performance and functions of our products.

In this talk I will briefly provide a social and ethical foundation for robotics. By drawing on sociological work on robotic companions and the use of robotics in art practice, I will draw out a set of dimensions for understanding robotics in social life. These naturally lead on to a program of engaged 'interactional' research, which supports both the recognition of the social issues and the ethical development of robotics in the future. Key is a recognition of the embodied and affective relations between human and machine in particular social contexts. For example, care of the elderly requires attention be paid to the experiences and expectations of not only the recipient of care, but also the existing social network of actors and institutions. It is through such insight that 'care' can be socially understood and ethically provided.

Marine protected areas (MPAs) are showing great promise as a way of the balancing the needs of conservation and fisheries around the world. However, MPAs need to be monitored and evaluated to ensure they are providing the benefits they have been designed to produce. The analysis of habitats and species inside MPAs has been largely been based on visual records to date, taken either during SCUBA diving surveys or from drop down Baited Remote Underwater Videos (BRUVs).
Although these methods have provided useful data, they both have their limitations; time and depth for divers and seabed area that can be monitored using BRUVs. The aim of this project was to examine the feasibility of replacing these methods with mobile underwater robots (Remotely Operated underwater Vehicles – ROVs) that would be able work at depths beyond the range of divers (>30m) and to move to many more points on the seabed, thereby covering large areas. Through the addition of sonar, it would also be able to gather data about the structure of underwater habitats. This information is critical for truly understanding fish-habitat relationships and therefore identifying which marine areas are in most need of protection.

On this basis we purchased an underwater robot (Blue Robotics BlueRov 2) equipped with sonar (Oculus M1200d Multibeam Sonar System). This ROV was trialled in a well-studied MPA off the Isle of Arran in Scotland during July 2019. Despite some technical challenges, the ROV successfully supplied live and recorded underwater images from significant areas of seabed. Likewise, the sonar was able to image the seabed at a range of up to 20 m underwater. The next step is to compare the quality of data supplied by the ROV with that from conventional methods. We plan to investigate signal processing techniques to infer the structure of the environment, through precise 3-D navigation, using data from the camera and sonar images. The same data will also be used to automate the counting of species by applying machine vision classification techniques. With these enhancements it will be possible to examine even greater marine areas in more detail than ever before.

The challenge I will discuss is achieving affordable certification of autonomous systems, rather than trying to lower the certification bar to make autonomous systems commercially viable. To this end, I shall discuss the background for the use of Automated Formal Methods in the context of DO-178C. In particular I will discuss the challenges of Regulation in order to fly an autonomous drone Beyond Visual Line Of Sight (BVLOS) outside segregated airspace and the report results of an Innovate UK project on BVLOS.

According to the traditional, instrumental theory of technology, technological artefacts and devices are nothing but tools, completely under the power of the people who make and use them. On this theory, moral responsibility for any ill effects of the operation of tools rests straightforwardly with their human makers and users. But autonomous systems stretch and challenge this traditional theory. Because of their sheer complexity, these systems may sometimes behave in ways that their human developers and users do not directly intend, cannot foresee, do not fully understand, and may not even be able to change in a timely and effective manner once underway – particularly when the systems interact with, and adapt to, other agents (both human and artificial) in their operational domain. This complicates ascriptions of moral responsibility on traditional grounds. In recognition of this fact, I argue that rather than look upon autonomous systems as mere tools, we should think of them as delegates, which we train up and to which we hand over decisional tasks. As such, we bear moral responsibility for the ill effects of their behaviour in much the same way that human principals bear moral responsibility for the ill effects of the execution of tasks that they delegate to human agents. The difference is that, unlike human delegates, autonomous systems are not moral agents, and so they cannot bear any moral responsibility themselves when things go wrong.

Image-guided therapy is a clinical procedure under 2-D or 3-D image guidance such as MRI, CT and Ultrasound images to accurately deliver surgical devices to diseased or cancerous tissue. This emerging field is interdisciplinary, combining the technology of robotics, computer science, engineering and medicine. Image-guided therapy allows more effective and accurate minimally invasive surgery and diagnosis. In this talk, Dr. Tse will present the technological challenges in the field, followed by his research in MRI-guided therapy for brachytherapy, ablation and stem cell treatment in the prostate, the heart and the spine. These procedures consist of the latest imaging and robotic technology in minimally invasive therapy.