Pedro Patron

David A. Robb, Jonatan Scharff Willners, Nicolas Valeyrie et al.

Autonomous underwater vehicles (AUVs) are being tasked with increasingly complex missions. The acoustic communications required for AUVs are, by the nature of the medium, low bandwidth while adverse environmental conditions underwater often mean they are also intermittent. This has motivated development of highly autonomous systems, which can operate independently of their operators for considerable periods of time. These missions often involve multiple vehicles leading not only to challenges in communications but also in command and control (C2). Specifically operators face complexity in controlling multi-objective, multi-vehicle missions, whilst simultaneously facing uncertainty over the current status and safety of several remote high value assets. Additionally, it may be required to perform command and control of these complex missions in a remote control room. In this paper, we propose a combination of an intuitive, natural language operator interface combined with communications that use platforms from multiple domains to relay data over different mediums and transmission modes, improving command and control of collaborative and fully autonomous missions. In trials, we have demonstrated an integrated system combining working prototypes with established commercial C2 software that enables the use of a natural language interface to monitor an AUV survey mission in an on-shore command and control centre.

Helen Hastie, Francisco J. Chiyah Garcia, David A. Robb et al.

We present MIRIAM (Multimodal Intelligent inteRactIon for Autonomous systeMs), a multimodal interface to support situation awareness of autonomous vehicles through chat-based interaction. The user is able to chat about the vehicle's plan, objectives, previous activities and mission progress. The system is mixed initiative in that it pro-actively sends messages about key events, such as fault warnings. We will demonstrate MIRIAM using SeeByte's SeeTrack command and control interface and Neptune autonomy simulator.

Francisco J. Chiyah Garcia, David A. Robb, Xingkun Liu et al.

Autonomous systems in remote locations have a high degree of autonomy and there is a need to explain what they are doing and why in order to increase transparency and maintain trust. Here, we describe a natural language chat interface that enables vehicle behaviour to be queried by the user. We obtain an interpretable model of autonomy through having an expert 'speak out-loud' and provide explanations during a mission. This approach is agnostic to the type of autonomy model and as expert and operator are from the same user-group, we predict that these explanations will align well with the operator's mental model, increase transparency and assist with operator training.