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AM Briefing: Autonomy and big data for defence
1) The document discusses using autonomy and big data to enhance military capabilities. It describes how military platforms could use prior environmental data to achieve greater autonomy. 2) Several challenges for military applications were identified, including operating in GPS-denied environments and dealing with threats. The discussion focused on acquiring and processing environmental data for autonomous vehicles. 3) Two specific challenges were outlined: sourcing big data in difficult, hostile environments with limited resources; and validating data from multiple sources that may be trusted, classified, unvalidated or open/ambiguous. Transforming intelligence using big data is seen as important for the future.
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AM Briefing: Autonomy and big data for defence
- 1. Innovation Network event 21October 2015
- 2. Jim Pennycook CDE Headof Operations
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- 4. The aim ofCDE
- 5. Rapid technology change Defence Othermarkets Utilisation
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- 7. CDE directive Prove thevalue of innovative, high-risk, high-potential-benefit research to enable development of cost-effective military capability advantage Defence White Paper – National Security Through Technology Feb 2012
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- 9. First point ofcontact ‘CDE remains our first point of contact for those who wish to submit a research idea to the MOD.’ Defence White Paper – National Security Through Technology Feb 2012
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- 18. Managing innovation Proof of concept Development InnovationFuture capability CDE MOD + investors
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- 20. Technology innovation lifecycle Originalidea Capability
- 21. Technology innovation lifecycle Uptake/ commercialisation Pre-commercial development TRL 1 TRL 2 TRL 3 TRL 4 TRL 5 TRL 6 TRL 7 TRL8 TRL 9 Experimental research Technology implementation Applied research Curiosity driven research
- 22. CDE competition space Pre-commercialdevelopment TRL 3 TRL 4 TRL 5 TRL 6 Applied research Solution exploration Prototyping/test products Phase 1 Phase 2
- 23. Phase 1 TRL 7 TRL 2 CDE competitionspace Phase 2 TRL 3 TRL 4 TRL 5 TRL 6
- 24. Two routes tofunding Enduring Themed Not classified Enduring competition Themed competition £ 7M
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- 27. Challenge framework ProtectionLethality Human performance Mobility Situationalawareness CommunicationData Power Lower cost of ownership
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- 29. Competitions this year ThemeValue Open-source big data insight £2.25M Persistent surveillance from the air £2.25M Agile, immersive training £2.25M What's inside that building? £1.15M Understand and interact with cyberspace £1.00M
- 30. Current competitions Theme Value Securityfor the internet of things £2M Autonomy and big data for defence £4M
- 31. Future competitions Theme Value Syntheticbiology for defence £2M Prevention and treatment of tinnitus £1M
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- 34. How has CDEperformed?
- 35. CDE in numbers 5938 proposalsreceived 57%
- 36. CDE in numbers 17% ofproposals funded 20%13% E T
- 37. CDE in numbers 934 contractsplaced 43%
- 38. CDE in numbers £57.9M invested 12 3 4 5 6 7 8
- 39. What’s next forCDE?
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- 41. Innovation Network events DateTheme 10 Feb 2016 Synthetic biology for defence 11 Feb 2016 Prevention and treatment of tinnitus Sign up to get updates
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- 45. Today’s competition Autonomy andbig data
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- 47. Innovation Network event 21October 2015
- 48. 21 October 2015 PaulWinstanley Simon Christoforato Paul Day UK Defence Solutions Centre “Spearheading Innovation in Defence Exports”
- 49. Page 50 Context Three majorparadigm shifts impacting defence: • Increasingly customers seek tailored solutions to meet their specific needs; especially through collaboration and partnership • To deliver the most effective defence capability the defence sector must harness technological innovation from all possible sources. • Need for innovative ways to fund investment for the development and delivery of future world class defence capabilities To address this we need a new approach to defence innovation
- 50. Page 51 The DefenceGrowth Partnership “UK Government and Industry working together to meet the needs of customers around the globe”
- 51. Page 52 A uniquepartnership between UK Government and UK defence industry We’re growing the UK defence industry making it a world leading centre of innovation We use an objective, market led approach to deliver unmatched international collaboration and innovation by bringing new, collective and impartial insight We work with: • International Governments • Defence Industry • Small & Medium Enterprises • Academia • Investors What is the UK DSC? “UK Value Chain”
- 52. Page 53 The GlobalMarket Opportunity 2
- 53. Page 54 UK DSCvideo
- 54. Page 55 Concepts & Solutions OurEcosystem Customer Requirements Analysis Emerging view of customer needs Opportunity to shape nascent customer thinking, show “art of the possible” and showcase “Big Ideas” Innovative Solutions thinking Informed by comprehensive view of UK capabilities Wider engagement in UK value chain brings new, preferably disruptive capabilities into the mix New, or enhanced capability required to meet market need is defined by gap analysis Enhanced capability “palette” from which to develop innovative solutions Capability Development Partnering Investment Interventions
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- 56. Page 57 Innovation • Defencewill not be the prime driver behind new developments • Opportunity to leverage technology base outside defence • Open Innovation • Sources • Building on work from the previous DGP activities, such as; - Intelligent Systems - UAS • Plus other UK initiatives such as - UK Eight Great Technologies
- 57. Page 58 Innovation ChallengeScope Persistent Surveillance Small SWaP Sensors Persistent Surveillance Data Analysis Deployable Autonomy Simulation & Training M o D Market Research I n d u s t r y External Innovations
- 58. Page 59 Innovation ChallengeScope Big Data For Defence Autonomy Persistent Surveillance Data Analysis Deployable Autonomy
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- 60. Innovation Network event 21October 2015
- 61. Dstl is partof the Ministry of Defence Autonomy and the military user Lt Col Andy Simpson RL SO1 Fighting Vehicle Systems Dstl 22 October 2015 Photo: Lockheed Martin
- 62. Dstl is partof the Ministry of Defence 22 October 2015 • SDSR 10. ‘We will continue the most essential investment in S&T. We will focus investment on developing capabilities and countering threats in key areas, such as autonomous systems, sensors, new materials including nanotechnology, cyber and space’. • Defence Strategic Guidance. ‘In aggregate, the 2015 SDSR work streams on capabilities, industry and exports must consider the role and effects of greater autonomy… gathering and countering intelligence in distributed networks and infrastructures, and open innovation’. Context
- 63. Dstl is partof the Ministry of Defence 22 October 2015 MOD’s Future Operating Environment 35 paper highlights the future importance of Robotic and Autonomous Systems. In doing so, it notes they are unlikely to replace service personnel in the near and medium term, rather they will augment their capabilities. Am I soon out of a job?
- 64. Dstl is partof the Ministry of Defence 22 October 2015 •Enhance C4ISTAR •Tasks within dirty and dangerous environments •Logistics support, including CASEVAC •Force protection tasks •Generate mass or multiple points of presence •Conduct dull tasks •Operating within/above/under structures Augment what sort of capabilities?
- 65. Dstl is partof the Ministry of Defence 22 October 2015 Photo: ASV
- 66. Dstl is partof the Ministry of Defence Why we are here today… 22 October 2015 •MOD will need to use autonomous vehicles in complex environments in the air, on land and at sea where there’s limited or out-of-date prior knowledge about the terrain or environment. •The autonomous vehicles will have on-board sensors but these may be limited by the need to be covert or to operate in harsh electro- magnetic environments, eg GPS degraded or denied environments.
- 67. Dstl is partof the Ministry of Defence 22 October 2015 Maybe not this….
- 68. Dstl is partof the Ministry of Defence 22 October 2015 But this….
- 69. Innovation Network event 21October 2015
- 70. UK OFFICIAL Autonomy andbig data for defence Challenge 1: acquiring data for autonomous vehicles Mark Emerton © Crown copyright 2014 Dstl 22 October 2015 21 October 2015
- 71. UK OFFICIAL Overview • MODautonomy research • Autonomy levels • Case study: civilian autonomous vehicles • Military constraints • What we want • What we don’t want © Crown copyright 2015 Dstl 22 October 2015
- 72. UK OFFICIAL MOD autonomyresearch: © Crown copyright 2015 Dstl 22 October 2015 Air LandNaval Ship Systems and Integrated Survivability Maritime Freedom of Manoeuvre Unmanned Aircraft Systems Defence Logistics and Support Land Environment Decision Support Knife / Academic Centre for Defence Enterprise Integrated Sensing Close Combat Systems
- 73. UK OFFICIAL Autonomy levels: ©Crown copyright 2015 Dstl 22 October 2015 ‘Traditional’ autonomy scale:
- 74. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 Autonomy Levels for Unmanned Systems (ALFUS)
- 75. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 Autonomy Levels for Unmanned Systems (ALFUS)
- 76. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 Case study: civilian autonomous car
- 77. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 Case study: civilian autonomous car
- 78. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 Case study: civilian autonomous car
- 79. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 Achieving more autonomy in military platforms (air, land and sea) can be achieved by providing timely and accurate ‘prior knowledge’ of the operating environment to simplify the local sensing and interpretation task Opportunity
- 80. UK OFFICIAL Known challenges •GPS-denied environments • Dependability of civilian infrastructure • Harsh electromagnetic environments • Cyber threats • Physical threats © Crown copyright 2015 Dstl 22 October 2015
- 81. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 - Methods of acquiring prior knowledge of environments for use by autonomous platforms, land, sea and air - Methods of processing data sets to simplify or enable their use by autonomous platforms - Methods of exploiting prior knowledge to achieve greater levels of autonomy in future platforms What we want:
- 82. UK OFFICIAL© Crowncopyright 2015 Dstl 22 October 2015 - Vehicle platform technologies (eg airframes or propulsion) - Platform architectures - Intent or threat profiling What we don’t want:
- 83. Innovation Network event 21October 2015
- 84. Simon Christoforato Head ofSolutions, UK DSC Autonomy – defence exploitation and exportability
- 85. Page 87 Autonomy –a UK strength Image: Transport Systems Catapult
- 86. Page 88 Defence exploitation- logistics Time Fully Autonomous vehicles Soldier resupply Logistic Convoy Part Task Autonomy Applique Kits Air Delivery …..Practical experimentation is key Images: Lockheed Martin Image: Boston Dynamics Image: Scania Image: Amazon Image: RDM Group
- 87. Page 89 Defence exportopportunities Image: IBTimesImage: QinetiQ
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- 89. Autonomy and bigdata for defence: Military overview Lt Col D W Somerville MBE BSc CEng MIET UK OFFICIAL
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- 91. How do we,the UK military, win? • In the past….. • In the current….. • In the future….. UK OFFICIAL
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- 93. Boyd’s OODA loop ObserveDecide Act Action (Test) Implicit Guidance & Control Implicit Guidance & Control Observations Unfolding Circumstances Outside Information Unfolding Interaction With Environment Unfolding Interaction With Environment Orientate Decision Feedback Feedback J. R. Boyd, “the Essence of Winning and Losing,” 1995. Cultural Traditions Genetic Heritage New Information Previous Experience Analyses & Synthesis Observe Decide Act Action (Test) Implicit Guidance & Control Implicit Guidance & Control Observations Unfolding Circumstances Outside Information Unfolding Interaction With Environment Unfolding Interaction With Environment Orientate Decision Feedback Feedback J. R. Boyd, “the Essence of Winning and Losing,” 1995. Cultural Traditions Genetic Heritage New Information Previous Experience Analyses & Synthesis Cultural Traditions Genetic Heritage New Information Previous Experience Analyses & Synthesis UK OFFICIAL
- 94. • 640 TBdata transferred every minute via internet; • Cost per Giga-FLOP: – 2000 - $1,300.00 – 2015 - $0.08 • 90% of world’s data generated in last 2 years • 1 Zettabyte per year generated by 2015 (to the moon and back in stacked CD’s) • ~ 290TB per hour generated by Wide Area Surveillance Sensors • ~10TB data per UAV sortie generated; • TB’s to PB’s of unstructured data (text, imagery, video, audio) generated on operations. UK OFFICIAL-SENSITIVEUK OFFICIAL
- 95. Boyd’s OODA loop ObserveDecide Act Action (Test) Implicit Guidance & Control Implicit Guidance & Control Observations Unfolding Circumstances Outside Information Unfolding Interaction With Environment Unfolding Interaction With Environment Orientate Decision Feedback Feedback J. R. Boyd, “the Essence of Winning and Losing,” 1995. Cultural Traditions Genetic Heritage New Information Previous Experience Analyses & Synthesis Observe Decide Act Action (Test) Implicit Guidance & Control Implicit Guidance & Control Observations Unfolding Circumstances Outside Information Unfolding Interaction With Environment Unfolding Interaction With Environment Orientate Decision Feedback Feedback J. R. Boyd, “the Essence of Winning and Losing,” 1995. Cultural Traditions Genetic Heritage New Information Previous Experience Analyses & Synthesis Cultural Traditions Genetic Heritage New Information Previous Experience Analyses & Synthesis UK OFFICIAL
- 96. Other factors • Legality– rules of engagement • Morality • Media • Political acceptability • Historical review • Public appetite UK OFFICIAL
- 97. Large-scale face recognition UK OFFICIAL-SENSITIVEUKOFFICIAL Big data vignettes
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- 99. Innovation Network event 21October 2015
- 100. Big data fordefence CDE competition: challenges 2-4 Duncan Abercrombie © Crown copyright 2014 Dstl 22 October 2015
- 101. Transforming the defenceintelligence community • How we traditionally conduct intelligence © Crown copyright 2014 Dstl 22 October 2015 SWORD beach - 6 Jun 1944 Chain Home Images from Defence Imagery Database
- 102. Transforming the defenceintelligence community • How we will conduct intelligence in the future © Crown copyright 2014 Dstl 22 October 2015 Image from Flickr. Credit: Christian Schnettelker www.manoftaste.de
- 103. Challenge 2: sourcingbig data in difficult environments • Variety of sources (on-board and off-board) • Low bandwidth • Hostile environment • Limited computing power • Few human resources • Firewalls / security © Crown copyright 2014 Dstl 22 October 2015 Images from Defence Imagery Database
- 104. Challenge 3: validatingsources of big data • There will be multiple sources of data: – trusted – classified – unvalidated – open and ambiguous • Decision making will require a confidence and reliability of all sources © Crown copyright 2014 Dstl 22 October 2015 Images from Defence Imagery Database
- 105. Challenge 4: managingand visualising big data • Collection systems will produce large volumes of data that could overwhelm analysts • Data will be from – Multiple sensors – Diverse sensors – Persistent sensors © Crown copyright 2014 Dstl 22 October 2015 Images from Defence Imagery Database
- 106. Innovation Network event 21October 2015
- 107. Paul Day Capability Development,UK DSC Big data for defence
- 108. Challenge 2: Sourcingin difficult environments The Adversary Information Assurance Image: CNMEonline Image: Raytheon. Image: Raytheon. Image: MOD, Crown Copyright
- 109. Challenge 3: Validatingsources
- 110. Challenge 4: Managingand visualising
- 111. Export and exploitation Image:iRevolution.wordpress.com. Image: iRevolution.wordpress.com. Image: Crown Copyright.
- 112. Innovation Network event 21October 2015
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- 114. Autonomy and bigdata How will the competition work?
- 115. What’s different? Autonomy andbig data
- 116. Technology challenges Proposed byUKDSC Meets MOD needs Funded by MOD
- 117. Who’s here andwhy? CDE Dstl UKDSC
- 118. Know who you’retalking to Face-to-face meetings In confidence NDA with UKDSC
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- 120. Technical partners Dstl personnel MODcontract UKDSC opportunities
- 121. Phase 1 Up to6 months Up to £100k Proof of concept
- 122. Up to £2million available 6 to 8 months duration Collaboration Phase 2
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- 129.
- 130. What do wewant?
- 131. Autonomy and bigdata Challenge Acquiring data for autonomous vehicles 1
- 132. Autonomy and bigdata Challenge Sourcing big data in difficult environments 2
- 133. Autonomy and bigdata Challenge Validating sources of big data 3
- 134. Autonomy and bigdata Challenge Managing and visualising big data 4
- 135. What we don’twant Paper-based studies Marginal improvements Limited benefit to defence
- 136. Project deliverables A soundbody of evidence Demonstration of deliverable Proposal for Phase-2 activity
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- 138. Start to placecontracts: Competition dates Early January 2016
- 139. Phase 1 researchdelivered by: Competition dates 30 June 2016
- 140. Marketplace and Phase2 funding decisions Dates July 2016
- 141. Competition closes 11 November2015 at 5pm Nov 5112015
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- 144. Innovation Network event 21October 2015