Explainable Autonomy in the Maritime Domain

Lead Research Organisation: Heriot-Watt University
Department Name: S of Mathematical and Computer Sciences

Abstract

Principal goal for project:
Enable effective text-based interaction between an operator and an AUV to unlock situation awareness in the underwater domain.
Research project:
Explanation of autonomous behaviour is motivated by the need for transparency in critical applications and remote isolation that operators go through during mission supervision. The domain is autonomous underwater vehicles (AUVs) where transparency is even more critical due to the intermittent communication with the vehicle, deep underwater. Data-driven techniques will be explored that allow text-based interaction between the autonomy engine and the operator. Data2Text is a field of Natural Language Generation that typically takes one data source such as time-series data for weather, finance, biosignals. Here, we will investigate Data2Text deriving text explanations but from a mix of structured and unstructured data in various formats including log messages, a world model and dynamic environment, status from the vehicle, as well as, a representation of the autonomy model logic. The aforementioned data would be used as input to an end-to-end model that analyses these features and learns their relation and generates a natural description of the vehicle activity, status, mission success as well any errors or warnings. Investigating hybrid models such as hybrid code networks that can integrate the hand-written rules of the autonomy model as well as argumentation will also be investigated.

Planned Impact

The Centre will have immediate short-term impacts on people skills and innovation pipeline, alongside key advances in scientific knowledge and techniques in Robotics and Autonomous Systems (RAS). With the strength of the programme's training emphasis on safety and responsible research and innovation (RI), we also target longer term economic and societal benefits.

Economy: It is estimated that the application of advanced robotics could generate a potential worldwide economic impact of $1.7-4.5 trillion by 2025 per year by 2025 (McKinsey). Over the last 5 years, the UK has witnessed significant new investments in robotics from both Government with the £4.7B Industrial Strategy Challenge Fund (ISCF), spawning parallel investments from industry. An example is the EPSRC £18M investment in the EPSRC ORCA Hub in RAS, led by Heriot-Watt, leveraging a further £18.5M industry investment. The potential economic impact of RAS, however, is hampered by a massive skills shortage, which the proposed CDT-RAS would address. The new jobs created by these investments will require highly specialised, yet interdisciplinary and industrially relevant skill-sets. The CDT-RAS is well positioned to supply the UK workforce in this growing area, through strong links with industry through its extensive CDT-RAS Project Partners network and through a training emphasis on 'innovation-ready' graduates. For example, our CDT-RAS students will have the opportunity to grow into industrial leaders of tomorrow through direct experience and company placements, as well as, through the CDT's extensive support for commercialisation and start-ups.

Society: Robotic and autonomous systems have already been identified by the UK government as a key component to enable safer working conditions for 'dull, dirty and dangerous' tasks in extreme and challenging environments such as offshore, nuclear, mining, and space. Moreover, there are disruptive opportunities for RAS to contribute to cost-effective and safer construction, transport, and manufacturing and improved quality-of-life through healthcare and assisted living. CDT-RAS training focuses on interdisciplinary, cross-cutting, yet responsible research and innovation to allow our future leaders to develop techniques and technologies that will have impacts in new areas, beneficially improving society beyond what we can already imagine. We will develop autonomous systems and AI enablers that are transparent to developers and end-users alike. This will allow robots and machines to work seamlessly in society both individually and in teams and comply with regulations, such as the EU General Data Protection Regulations (GDPR) and emerging IEEE standards, such as P7001 for Transparency for Autonomous Systems (for which Centre academics are members of the working group).

Science: CDT-RAS students will benefit from i) a critical mass of over 50 experienced supervisors, ii) the brand new facilities of the £27.5M National ROBOTARIUM and earlier £8M EPSRC equipment investments, as well as, iii) opportunities for international scientific and industrial lab placements. The Centre will realise scientific advancement and impact, crucial to enabling safe interaction between RAS, humans and the environment, including soft robotics, bio-inspired systems, human-robot interaction, swarms and collaborative robotics including human-robot teaming, sensing, embedded control, multi-agent decision making and maritime field robotics. The impact of the resultant research will be strengthened through top-venue publications and conference presentations, utilising student presentation/writing skills honed during the CDT-RAS training. Impact will also come through outreach such as international student robot competitions, public engagement activities such as science festivals and CDT-RAS hosted international researcher visitors and workshops.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023208/1 01/10/2019 31/03/2028
2270306 Studentship EP/S023208/1 01/10/2019 08/03/2024 Konstantinos Gavriilidis