collaborative operations in denied environment … documents/2016 is... · collaborative operations...

Collaborative Operations in DeniedEnvironment (CODE) Program Overview

Jean-Charles (J.C.) Ledé, Program ManagerTactical Technology Office (TTO)

April 18-19, 2016

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Briefing Prepared for SPIE Defense + Security Symposium –Sensors and Command, Control, Communications and Intelligence (C3I) Technologies

for Homeland Security, Defense, and Law Enforcement Applications XV Conference

Distribution Statement A: Approved for Public Release, Distribution Unlimited

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Operating in the Emerging Denied Environment

EMS: Electro-Magnetic Spectrum

Stealth

Speed

Numbers

Poison (EW)

Collaboration

Long Distances

Contested EMS

Mobile Targets

High Threats

Integrated

Decoys


Capability• Developed against three reference missions (tactical recon

against AAA, DEAD, ASuW)• Algorithm effectiveness demonstrated in flight using 6 RQ-

23 Tigersharks and N virtual assets for one mission• Effectiveness demonstrated in simulation using operational

platforms for all reference missions

Get access Find target Identify target “Survive” engagement

Reduce overkill/underkill

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CODE: Program Overview and Vision

Envisioned Benefits for Strike Missions in Denied Environments

Collaborative Operations in Denied Environment (CODE) Vision• Develop advanced autonomy algorithms and supervisory

control techniques• Enhance utility of legacy unmanned aircraft (UA—missiles or

UAV) in denied environments• Foster interoperability of heterogeneous systems

CODE seeks to improve ability of existing arsenal to perform in denied environments

AAA: Anti-Aircraft Artillery, ASuW: Anti-Surface Warfare, DEAD: Destruction of Enemy Air Defenses, UAV: Unmanned Aerial Vehicle, UAS: Unmanned Aircraft System, UA: Unmanned Aircraft


Artist’s Concept

Four Pillars, Three Missions, Spiral Development

Anti–Surface Warfare

Collaborative Autonomy

Vehicle-Level Autonomy

Supervisory Interface

Open Architecture for

Distributed System

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Armed Reconnaissance

Destruction of Enemy Air Defense

Artist’s Concept

Concept validationthrough simulation

- operational system design

- critical technology

development

FY15

FY16

FY17

FY18

Phase 1

Phase 2

Phase 3

Initial S/W development limited flight

test with 1 or 2 A/C

End-to-end flight demo using 6 live +n virtual

assets emulating GPS and commsdenial

Artist’s Concept

Distribution Statement A: Approved for Public Release, Distribution UnlimitedPlanned schedule

Open Mission Systems

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• Collaborative sensing tactics• Collaborative strike tactics• Collaborative communication tactics• Collaborative navigation techniques• Formation flight• Multi-constraints auto-routing• Bandwidth reduction

• Mission-sensitive compression• Value of information• Health monitoring• Behavior modeling

Advancements in Autonomy

Targeting

Airborne relay

Mobile control station

Manned-unmanned teaming

Coordinated support

Multi-INT search and track

Artist’s concepts


Collaborative landmark-based navigation

Artist’s Concept

Distribution Statement A: Approved for Public Release, Distribution Unlimited 6

Algorithm Enhancements

Coherent beam formingAirborne relay

Communication strategiesArtist’s Concept

• Relative nav using time difference of arrival (TDOA)

• Coordinated Time of Arrival (CToA)• Collaborative Automatic Target

Recognition (ATR)• Coherent beamforming• Formation flight tested last year

under highly constrained communications


Advances in Human System Interface (HSI)

Key Enabling Capabilities

• Natural multimodal interaction fuses touch/voice• Understanding commander’s intent• Contextual interaction• Uncertainty representation• Decision aids• Target classification requests• Team and sub-team visualization• Tasking at the team and sub-team level• Define system authority or level of autonomy• Visual and audio alerting

CODE HSI seeks to elevate the mission commander to a supervisory role


Pre-Mission Planning and Preview

• CODE HSI provides MC with probabilistic mission plan critiquing and patching optimized against MC-specified parameters

Mission plan preview• Enables the mission commander (MC) to

visually inspect mission plans highlighting spatial, temporal, and logical relationships

• Provides MC with a ‘what-if’ capability where s/he may vary parameters such as:

• Number/types of assets employed• Tactics/plan templates employed• Planned contingencies

CODE pre-mission planning enables MC to simulate mission plans prior to launch

• Leverage a broad community of interest in developing autonomy• Create an environment for continuous improvement and open competition with no

barriers to entry• Exploit ongoing government-industry open architecture development

Why Open Architecture for CODE?

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• An open architecture for the CODE system seeks to enable:

• Adaptability• Rapid integration• Transition through testability, White Force

Network (WFN)

• White Force Network enables injection of:• Virtual air vehicles (AV), virtual threats, and

virtual targets• Mission contingencies

• Simulated loss of GPS and/or communications

• Other mission failures simulated

Artist’s Concept


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CODE White Force Network (WFN)

• Objective: Construct necessary test infrastructure to perform a robust, disciplined flight test of autonomous systems that can assess maturity and increase confidence in modeling and simulation based analysis

• Unique test challenges• Surrogate platforms — low-cost, modular, reusable, wide range of performance envelopes• Autonomy scaling — provides autonomous system under test with realistic timelines and data by

scaling platform speeds, time to target, sensor quality, platform dynamics, comms quality, etc.• Data collection — truth vs. sensed data across multiple platforms/sensors; time correlation

• Design:• Ties live RQ-23s w/high fidelity virtual & constructive

RQ-23s running same CODE software• Virtual RQ-23s on CODE team with live RQ-23s

• Ties live & virtual targets/threats seamlessly• Real RQ-23s can “see” virtual targets

• Ability to alter perceived test conditions for CODE team members

• GPS and communications jamming• Altering air vehicle health and status

• Ability to insert contingencies real time at the subsystem, system, sub-team, team, and world levels

• Leverages open architectureDistribution Statement A: Approved for Public Release, Distribution Unlimited


Fast Lightweight Autonomy (FLA)

Mr. Jean-Charles (JC) LedéProgram Manager, Defense Sciences Office (DSO)

August 2, 2016

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What Are We Trying To Do?

Program Goal: Develop minimalistic algorithms for high-speedautonomous navigation in cluttered, unfamiliar environments

Objective: Autonomous navigation of complex, urban, cluttered environment at 20m/s, with range up to 1km range during a 10-minute mission, with 20 W computing, without high-quality prior knowledge, without comms to operator, and without GPS

Common Test Platform:• Inexpensive, commercial off the shelf

(COTS) unmanned aerial system• Open source autopilot• Thrust/Weight ratio: 2.8• Fits through doors, windows


©DJI

Photo Illustration


FLA – New Approaches and Outcomes

• Behaviors – Develop tightly coupled control algorithms for extreme maneuverability required to fly through windows, doors, confined spaces

• Representation – Explore time-to-contact and topological connectivity knowledge representations rather than volumetric grid of spatial layout

• Perception – Algorithms to quickly recognize previously visited areas using room features to answer “have I been here before?”

• Use only post-hoc analysis of data to reconstruct features, create maps, etc.

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COTS i7 Processor- Algorithms- Control

COTS Camera - High frame rate- Global shutter- Obstacle detection

COTS Single Point Laser Range Finder

- Altitude

COTS Pixhawk Autopilot

- Low level control- Safety

COTS Inertial Sensor

- Pose- Odometry

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Example Flight Platform


• Autonomous flights demonstrated:• Obstacle detection and avoidance• Fast reactive behaviors• Robustness to a wide variety of

complex surfaces and textures• Ability to perceive, plan and navigate toward a vaguely-defined distant goal at ~2

m/s average speed

• For comparison, human baseline runs were teleoperated using first-person video

FLA Example Flights – Warehouse Experiment

Autonomy: 2.1 m/s

Human: 2.0 m/s


FLA Warehouse Experiment Speeds

• Autonomy was slower than humans on simple courses, but slightly faster on two more complex tasks

• Autonomy was generally less robust in completing tasks (57% vs. 78%)

• Autonomy speeds show significant improvement over the 2014 state of the art (1 m/s)

• Performers reported 10 m/s and 15 m/s peak speeds, up to 6 m/s2 acceleration

Autonomous System

Human Baseline


FLA Program Schedule

Broad Area Announcement15-16

AutonomousFlightPhase 2

ProgramManagement

Technical Interchange Meetings

Awards,Kickoff

Downselectperformer teams

Phase 1

Q1 Q2 Q3 Q4

FY15Q1 Q2 Q3 Q4

FY16Q1 Q2 Q3 Q4

FY17Q1 Q2 Q3 Q4

FY18

Phase 2

Q1 Q2 Q3 Q4

FY19

Test &Evaluation

AutonomousFlightPhase 1

Low-clutterMission Capability

Develop algorithms, behaviors (2 teams)

High-clutter Mission Capability

Develop representations, algorithms(3 teams)

IndoorWarehouse

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C3D – Centralized Control of Commercial Drones

Mr. Jean‐Charles LedéDr. Daniel Patt

Distribution Statement A – Approved for public release, distribution unlimited. 17

Concept OverviewAugust 2016

With access to the same global COTS drone parts bin, how can we have superior capability?

C3D objective:deliver superior tactical

warfighting utility to small units by developing framework and

applications that enablehigh level military‐specific tasking of multiple consumer drones

Key insight: military‐developed control algorithms and capabilities hosted in the hive will be able to control any COTS drone with only custom‐built interfaces. High re‐use in Government‐owned architecture would enable marketplace approach for military‐specific capabilities.

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C3D Goal: Superior capability through architecture and ecosystem

High-level tasking

COTS – Commercial-off-the-shelfDistribution Statement A – Approved for public release, distribution unlimited.

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Four exemplary vignettes needing multiple air vehicles, central coordination

Locate / Track Distributed Communication Network

Precise Mapping / Targeting / DesignSentry Functions

Distribution Statement A – Approved for public release, distribution unlimited.

www.darpa.mil

20Distribution Statement A: Approved for Public Release, Distribution Unlimited

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