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Collaborative Intent Exchange Based Flight Management System with Airborne Collision

Avoidance for UAS Emre Koyuncu*, Cengiz Pasaoglu**, Prof. Gokhan Inalhan*

*Istanbul Technical University **DHMI, General Directorate Of State Airports Authority

and Navigation Service Provider Turkey

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INSTITUTONAL BACKGROUND

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Aeronautics Research Center

• Central Laboratory for Aeronautics Research (2012-) – +7 Faculty, 15 Research Associates, +20 Ph.D. Level

Researchers • Established to promote advanced, interdisciplinary and

experimental research • Research Focus on wide spectrum of Aeronautics

Technologies • Design of manned and unmanned air vehicles,

spacecraft and spacecraft systems • Air Transportation, ATM • Flight Controls, Simulation and Avionics, • Nanoengineered Composites • Engine technologies and combustion • Aerodynamics, Aeroelasticity

• Strong outreach at both university, national and international level

– Nanotechnologies and Material Sciences – Electronics and Computer Science

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Research Partners and Sponsors

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Controls and Avionics Laboratory • Research Focus

– Advanced flight controls and avionics technologies – Unmanned air vehicles design and autonomy – Air Transport and ATM – Spacecraft Systems Design – Data Analytic Modelling, Estimation, Control and

Learning • Notable Achievements

– Designed the first Turkish indigenous commercial avionics systems 2006-2009

– Designed and built the first Turkish university-level autopilot system for UAVs. 2006-2009

– Designed and built the first Turkish University picosat : ITUpSAT I (TUBITAK) 2006-2009

– Designed and built indigenous bus and ADCS components for nano and micro-satellites ITUpSAT II (TUBITAK 108M523) 2009-2012

– Winner of AIAA/AAS Cansat Picosat Competion 2011

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UAS RESEARCH

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TURAC : Environmental Monitoring UAV

TURAC Configuration

Wingspan 4.2 m

Total Length 1.8 m

Height 1.05 m

Front Propeller Diameter 0.43 m

Empty Weight 39 kg

Maximum Takeoff Weight 47 kg

Havelsan-ITU Project

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TURAC : Environmental Monitoring UAV

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TURAC : Environmental Monitoring UAV

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4D TRAJECTORY MANAGEMENT

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Flight Deck Automation Support with Dynamic 4D Trajectory Management

Short-Term Collision Avoidance – for midair and terrain collision Probabilistic (multi threat) midair and terrain collision monitoring

Fully automated flight control take-over implementation for delayed pilot response

Certifiable Pseudo-random/probabilistic algorithms with modal maneuver approach

Collaborative Tactical Planning – for dynamically changing environmental/operational conditions and use of airspace

Intent based collaborative decision making with the ATC (high level language – FIDL)

On-board tactical conflict monitoring and resolution via air/air link (low level language – AIDL)

Incorporating all tactical level information through air/ground data link + on-board sense

Automated

Required response time is short

Visual Decision Support Tools Novel touch screen enabling synthetic vision screens increasing situational awareness

Integrated information visualization with trajectory planning modules

Head-Up Displays with augmented reality add-ons

Collaborative

Required response time is long

Human Centered Tools

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Advanced Flight Deck Automation Systems

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ITU B737-800NG Flight Deck and Novel Decision Support Systems

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FUTURE OF UAS

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World Outlook

• 82 Billion Dolar Economy in between 2015-2025 (AUVSI)

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Military and Civilian Market Growth

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UAS Market Composition

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Motivation

• Future intensive use of UAVs for civil applications will require integration into national airspace

• Major challenges; – Lack of UAS interaction links with Air Traffic

Management System – Non-standardised performance/behavioural

characteristics of vehicles • Unable to build a TCAS library based on

performance classification

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Motivation

• Next Generation UAV Flight Management Systems should include;

– Additional data links makes UAVs visible in 4D

• machine-to-machine communication – air to air data links

• machine-to-human(operator, traffic controller etc.) communication – air to ground data links

– Multi-layered safety system for long term and short

term conflict avoidance • Tactical real-time aircraft separation • Short term sense-and-avoid

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UAS Integration into NAS

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Intent Based Nominal Operation And Trajectory Planning

Machine-to-machine

Machine-to-human

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MICRO UAS INTEGRATION TO NAS : ARCHITECTURES

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KAMPUSIHA – UAS for Campus Security

Quadrotor UAV developed at ITU ARC With onboard camera, flashlight and siren

GUI Integrated into ITU Campus Security System for dispatching UAVs based on emergency calls

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IHATAR – UAS for Crop Monitoring

Flight Management Architecture Processed Images of the crop obtained from the onboard multispectral camera

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Integration of Micro UAS’ into the NAS

• High power/high weight manned aircraft type integration is not realistics

• Ever growing interest in Civilian Usages of UAS (Amazon, Google, and even Apple…) – Part of G type airspace usage (1200 ft and below)

• FAA 400ft proposition (500ft mandate for small UAVs)

• 3 Critical (and Main) Factors in real integration – Sense-Avoid Technologies (including geo fencing) – Tracking Technologies – UAS Recovery System : Minimal 3rd part damage/harm in

UAS failures

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UAS Integration via GSM

• Command control via GSM data link

• Sense and Avoid via GSM data link (ADS-B, ADS-C applications)

• Reservation basis restricted areas and broadcasting via GSM network

– Urban areas – Digital Elevation

Maps – Buildings – No fly zones – …

• Positioning via GSM Network

– Differential GSM positioning applications

• Traffic data cloud binding – Track UAS traffic

trough GSM Network

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UAS Integration via GSM

• Command control via GSM data link

• Sense and Avoid via GSM data link (ADS-B, ADS-C applications)

• Reservation basis restricted areas and broadcasting via GSM network

– Urban areas – Digital Elevation

Maps – Buildings – No fly zones – …

• Positioning via GSM Network

– Differential GSM positioning applications

• Traffic data cloud binding – Track UAS traffic

trough GSM Network • Redundancy through LOS

Data Link for C2

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UAS Integration via GSM

• Command control via GSM data link

• Sense and Avoid via GSM data link (ADS-B, ADS-C applications)

• Reservation basis restricted areas and broadcasting via GSM network

– Urban areas – Digital Elevation

Maps – Buildings – No fly zones – …

• Positioning via GSM Network

– Differential GSM positioning applications

• Traffic data cloud binding – Track UAS traffic

trough GSM Network • Redundancy through LOS

Data Link for C2 • Redundancy through

transponder for ADS-B

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EXPERIMENTAL DEMONSTRATION

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ITU Multirotor : Experimental Platform for Advanced Flight Controls and Autonomy Research

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Onboard Flight Management System

General Architecture of the FMS

Air-to-air data link (ADS-B emulator for air-to-air)

Air-to-ground Data Link

Flight Control Computer

Flight Management Computer

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Experimental Implementation

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Autonomous Sense And Avoid

The Sense and Avoid module • independent safety assurance system from the ground for short

term collisions with – the aircraft in the surrounding traffic and – terrain objects

• Do not use intent sharing or time-consuming negotiation processes,

and immediately intervenes when the midterm separation assurance process fails.

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Collision Avoidance Approaches

• Nominal models – only consider current behavior and updates

advisory upon each information availability – do not require detailed performance models – i.e. TCAS

• Probabilistic models – robust due to accounting for likelihood of all

possible future trajectories – generate high rate deviation maneuvers – require detailed performance model for all type

of aircraft • Worst case models

– consider worst case maneuvers minimizing collision time, then maximize first potential collision times

– computationally complex, therefore generally utilize finite maneuver libraries

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Autonomous Sense And Avoid

The sense and avoid module of the UAV uses two types of information:

– Surrounding traffic information • obtained from ADS-B (Automatic

Dependent Surveillance-Broadcast ) transponders of surrounding aircraft.

– Terrain database

• spatial model of the earth objects in certain resolution.

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Autonomous Sense And Avoid

ADS-B hardware emulator • Xtend 900 MHz RF Module • Pre-programmed to work in broadcast

mode • Communicate with all transponders in the

field • Enables both ADS-B In and ADS-B Out

applications For simplification, the experimental ADS-B transponder always use a single mode.

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Autonomous Sense And Avoid

ADS-B emulator message structure • An simplified ADS-B data structure • Covers most essential flight information with 56 bytes data

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Collision Detected

These are sent to the RRT*

b. Collision is detected at time t. c. RRT* algorithm is initiated. a. Pre-loaded tasks are in progress.

Cost Efficient Route

d. Cost efficient route is calculated by RRT* e. New route is transferred to UAV f. Task progress continues.

Search Area

New Route

Estimated Route Of Intruder

Conflict Detection and Resolution

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Real Time Video & Telemetry

Window

Speed

Altitude

Vertical

Speed

Artificial

Horizon

User Inputs

Home Position Mission

Control & Sense And

Avoid Window

Intruder Uncertanity

Balls

Altitude Window

Extra Information

Window

Current Waypoint UA

V

Estimated Route Of Intruder

Vehicle Selector

Route

ID, Altitude Difference, Heading

Altitude[m] Of Mission Step

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Intruder

Experimental Demonstrations

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Predicted Intruder Path

Updated Reference Trajectory

Intruder Uncertainty

RRT* Search Graph

t=0 sec

Position Error

Potential Collision Point

Reference Trajectory

Target Waypoint

Altitude History Target Altitude

Current Altitude

t=20 sec t=60 sec

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Thank you.