The UK Ministry of Defence (MoD) is soliciting proposals for novel concepts aimed at integrating 'intelligent systems' into future warships.
Being competed through the MoD's Defence and Security Accelerator (DASA) programme, the Intelligent Ship programme is seeking to mature innovative technologies and techniques applicable to ship classes in the 2040+ timescale. A budget of GBP1 million (USD1.3 million) is available to fund multiple Phase 1 proposals, with an additional GBP3 million potentially available to fund follow-on phases.
Released on 12 June, the Intelligent Ship competition document has set out to de-risk and evaluate technologies and approaches that could enable alternative, revolutionary future fleet concepts that can maintain or enhance UK military advantage. "This aim is based on a future vision where elements of automation, autonomy, machine learning and artificial intelligence [AI] are closely integrated and teamed with human decision makers," said the MoD. It added, "It is expected that this will ensure timely, more informed and trusted decision making and planning, within complex, cluttered, contested and congested operating and data environments."
Phase 1 proposals are sought to improve automation, autonomous functions, AI-enabled decision aids, or alternative human-machine interfaces, and how they could improve speed and/or quality of decision-making and mission planning in a future operating environment. Proposals may also aim to demonstrate innovative system and platform design options that could enable the exploitation of intelligent systems in alternative platform concepts.
The competition document has set out six specific 'challenge' themes: mission planning and decision aids, information fusion, sensor and information management, novel human-machine interfaces, human-machine teaming (applied to challenges 1-4), and integration.
Phase 1 submissions are due on 23 July. Potential further phases are expected to include the development of an evaluation environment to enable demonstration of quantification of the selected intelligent functions.
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