An Architecture for Seamless Integration of UAS-based Wildfire Monitoring Missions
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1 An Architecture for Seamless Integration of UAS-based Wildfire Monitoring Missions UNIVERSITAT POLITÈCNICA DE CATALUNYA ICARUS Research Group April'08
2 Outline Presentation of ICARUS Research Group Motivation System Technologies and Architecture Application Scenario: Wildfire Conclusions 2 Remote Sensing, Salt Lake City, April 2008
3 ICARUS Research Group Technical University of Catalonia at Barcelona 15 schools: EPSC 40 departments: DAC students PDI Castelldefels School of Tech. Electrical Engineering Aeronautic Engineering students Computer Architecture Dep. 120 PDI ( BSC ) High Performance Computes Network Distributed Applications 3 Remote Sensing, Salt Lake City, April 2008
4 ICARUS Research Group ICARUS Intelligent Communications and Avionics for Robust Unmanned aerial Systems 4 E.Pastor (Ph.D.), C.Barrado (Ph.D.), M.A. Peña(Ph.D.), J.López, X.Prats, J.Ramírez, P.Royo E.Santamaria Remote Sensing, Salt Lake City, April 2008
5 ICARUS Research Group Computer Sciences web services embedded programming and compilers GIS formal methods and verification Electrical Engineering WiFi, WiMax, RC, Satellite Electronic board design Aeronautics Engineering navigation aeronavigation procedures certification 5 Remote Sensing, Salt Lake City, April 2008
6 ICARUS Research Group Shadow UAV 5,5m AP04 6 Megastar RC 2,5m Remote Sensing, Salt Lake City, April 2008 Flir A320
7 ICARUS Research Group Main resources 7 Remote Sensing, Salt Lake City, April 2008
8 Outline Presentation of ICARUS Research Group Motivation System Architecture and technologies Application Scenario: Wildfire Conclusions 8 Remote Sensing, Salt Lake City, April 2008
9 Motivation State of the Art in application of UAS: Firebird 2001: Fire Fighting Management Support System ERAST / FiRE: NASA Project Design WRAP: NASA / US Forest Service Project Fire detection by Szendro Fire Department, Hungary NASA Dryden Flight Research Center 9 Remote Sensing, Salt Lake City, April 2008
10 Firebird 2001 MALAT Division of Israel Aircraft Industries Demonstrated a system capable of fire monitoring during 1996 based on the Firebird and Heron platforms: Firebird: Payload 25 kg, endurance 5 h cruise 60 KIAS, operating altitude 15,000ft. Heron: Payload 250 kg, endurance 40 h cruise 80 KIAS, operating altitude 35,000ft. 10 Remote Sensing, Salt Lake City, April 2008
11 ERAST / FiRE NASA Project ERAST (Environmental Research Aircraft and Sensor Technology) / FiRE Develop and flight-demonstrate UAVs for costeffective science missions ALTUS-II Payload 150 kg, endurance 12 h cruise 65 KIAS, operating altitude 30,000ft. ALTAIR scientific variant of the PREDATOR-B Payload 340 kg, endurance 32 h cruise 151 KIAS, operating altitude 50,000ft. 11 Remote Sensing, Salt Lake City, April 2008
12 WRAP NASA Project WRAP (Wildfire Research and Applications Partnership ) Real fire monitoring missions over the USA west-coast ( AIRDAS ) Airborne InfraRed System Thermal scan bands: ( 0.68 ( ( ( ( 5.50 ( ( 13.0 ( Calibration: IR +600 C. FOV: 108 degrees. Scan Rate: 4-23 scn / sec., Resolution: 8m at 10Kf 12 Remote Sensing, Salt Lake City, April 2008
13 Szendro Fire Department, Hungary Small UAS used for early fire detection: Low cost, simple approach Fire department integrated UAV 13 Remote Sensing, Salt Lake City, April 2008
14 Motivation Market will be driven by the end user requirements and applications Operational and acquisition costs when compared with an alternate method of completing the same mission will determine the level of success for civil applications Access to NAS no expected until 2015 Earth Observation and the Role of UAVs, a Capability Assessment, NASA DFRC, Ago'06 14 Remote Sensing, Salt Lake City, April 2008
15 Motivation Market will be driven by the end user requirements and applications --> Requirements Operational and acquisition costs when compared with an alternate method of completing the same mission will determine the level of success for civil applications --> Small UAV and Open Architecture Access to NAS no expected until > Remote operations: Wildfire missions --> and... collaboration with local firemen 15 Remote Sensing, Salt Lake City, April 2008
16 Outline Presentation of ICARUS Research Group Motivation System Technologies and Architecture Application Scenario: Wildfire Conclusions 16 Remote Sensing, Salt Lake City, April 2008
17 System Technologies Firemen requirements: GRAF System Architecture Communication Gateway Mission: HMI and End User Procedures 17 Remote Sensing, Salt Lake City, April 2008
18 Geographical situation Fire extinction responsibility is decentralized by regions. Inter-region / central government cooperation available if necessary. Area: km2 Population: Fires during 2006: 629 Burnt area: ha Worst year (1994): ha 18 Remote Sensing, Salt Lake City, April 2008
19 Available aerial resources 19 Remote Sensing, Salt Lake City, April 2008
20 Aircraft operation schemes Surveillance and attack airplanes follow predefined routes around the clock during daytime. In case of detection first retardant attack is executed Rest of available units are used on demand. No flying during night time. 20 Remote Sensing, Salt Lake City, April 2008
21 Conditionings Geographical application area: Relatively small area; operations under responsibility of local government and therefore with limited budget. Externalized aerial resources except C&C helicopters. UAS to be operated by external providers. Integration with fire fighters own systems: Aerial operators see opportunities but do not want to see a UAS mixed in their airspace!! Ground firefighters are eager to receive any available technology innovation. Even though existing legal limitations and pilots opposition, ground firefighters suggest several application scenarios with strict manned/unmanned separation. 21 Remote Sensing, Salt Lake City, April 2008
22 Proposed lines of work Identify effective application scenarios Contacts with many fire fighter organizations Application scenarios change depending on user capabilities and geographical conditions Human-Machine Interface critical for non-it users Identify operational and information flow and implement the technology to support Highly dependent on the selected autopilot Information flow management exploitation: key points to create an usable system for non-it users 22 Remote Sensing, Salt Lake City, April 2008
23 Proposed system architecture Oriented to mission management and information flow. Real Time Data Acquired and Distribution System divided into four components: UAS: designed for data acquisition and autonomous operation. Mobile Control Station: responsible for UAS tactical control (flight operations), data gathering and processing. Squad Information Terminal: provides information to the ground crew. Data Processing Center: strategic control of multiple ongoing operations, data storage for post-fire analysis, highlevel coordination and decision center. 23 Remote Sensing, Salt Lake City, April 2008
24 Proposed system architecture UAS components: Airframe Flight Control System Payload Payload/Mission Control System Communication System 24 Remote Sensing, Salt Lake City, April 2008
25 UAS Architecture z z 25 Network Centric with data Publish/Subscribe Services may be producers and/or consumers Remote Sensing, Salt Lake City, April 2008
26 GCS and Squad Systems 26 Remote Sensing, Salt Lake City, April 2008
27 CPD System 27 Remote Sensing, Salt Lake City, April 2008
28 UAV Service Abstraction Layer 28 Remote Sensing, Salt Lake City, April 2008
29 Communication Gateway z z 29 makes service location is irrelevant monitors links to provide cost effective QoS Remote Sensing, Salt Lake City, April 2008
30 Example of Mission Services z 30 Mission is formally specified through visual tools: Relations between services are specified by flow diagrams Dynamic activities through event-based systems. Remote Sensing, Salt Lake City, April 2008
31 Benefits of network centric / SOA Dynamic service discover Services can be identified when the system goes online or later during operation. Remote execution Consumer simply sends a service request and its parameters. Later on it will get results. Self-description Each module provides a description of the services that it can provide. Services may shut down or be set up dynamically. Multiple equivalent services may be available adding a level of redundancy. Data streaming Semantic publish/subscription mechanisms for high change rate data 31 Remote Sensing, Salt Lake City, April 2008
32 Mission The mission is a set of services that orchestrate the whole operation of the UAS. Link the flight plan that the UAS follows and the operation executed by the payload. Mission may dynamically change as fire evolves, therefore updated flight plans should be computed. Given that operational requirements change from mission to mission, additional or improved quality payload can be added just by including new or inherited services. 32 Remote Sensing, Salt Lake City, April 2008
33 Mission procedures Previous to flight: mission definition During flight (in parallel): ( redefinition Exploration (flight area Data processing Data Presentation Data Storage After flight: Data post-processing 33 Remote Sensing, Salt Lake City, April 2008
34 Mission procedures Previous to flight: mission definition During flight (in parallel): ( redefinition Exploration (flight area Data processing Data Presentation Data Storage tactical After flight: Data post-processing scientific Man in the loop: HMI functionalities 34 Remote Sensing, Salt Lake City, April 2008
35 Mission Roles Responsible: Decision maker Data Presentation Mission Operator Definition Exploration Others Pilot-in-command Maintenance 35 Remote Sensing, Salt Lake City, April 2008
36 Parametric Flight Plan Definition Continuous scan is necessary to follow fire perimeter. 36 Remote Sensing, Salt Lake City, April 2008
37 Parametric Flight Plan Definition Mission control allows to design a service that identifies fire perimeter Exploration area is dynamically changed by updating a few flight plan parameters. 37 Remote Sensing, Salt Lake City, April 2008
38 HMI Flight Plan Definition 38 Remote Sensing, Salt Lake City, April 2008
39 Intelligent Flight Plan Service Dynamic adaptation 39 Remote Sensing, Salt Lake City, April 2008
40 Intelligent Flight Plan Service Dynamic adaptation 40 Remote Sensing, Salt Lake City, April 2008
41 Intelligent Flight Plan Service Dynamic adaptation 41 Remote Sensing, Salt Lake City, April 2008
42 HMI Flight Plan Exploration / Presentation 42 Remote Sensing, Salt Lake City, April 2008
43 Outline Presentation of ICARUS Research Group Motivation System Technologies and Architecture Application Scenario Conclusions 43 Remote Sensing, Salt Lake City, April 2008
44 Application Scenarios GRAF identified three viable fire missions: Monitoring of prescribed burnings for security and fire behaviour post analysis Final fire mop-up with hot-spots detection Fire monitoring during night Based on the following characteristics: Detection is not a goal in populated areas No interference with standard air-planes High cost of alternate solutions Progressive complexity 44 Remote Sensing, Salt Lake City, April 2008
45 Some numbers Mean of burned surface per wildfire is 6Ha FLIR A320 camera characteristics: 320 x 200 pixels At 100 AGL: image is 40 x 30 m ---> 1 pixel = 0.02 square meters Frequency rate up to 9Hz UAV flight characteristics 100 meters AGL speed 60Km/h ---> Aprox. 3 minutes flight to scan 6Ha 45 Remote Sensing, Salt Lake City, April 2008
46 Conclusions ICARUS group research topics and proposals for (small) UAS Hardware/Software embedded architecture Human-Machine Interfaces End Users Requirements and Procedures ( future ) Integration of UAV in air space Forest fire is an target civil application for: Segregated airspace UAS operation is cost effective Commercially viable 46 Remote Sensing, Salt Lake City, April 2008
47 Conclusions Not all geographical scenarios are equivalent; countries with large unpopulated areas may require emphasis in detection Other applications (fire perimeter detection, crop monitoring, rescue of lost people,...) need a previous successful stories 47 Remote Sensing, Salt Lake City, April 2008
48 Muchas gracias 48 Remote Sensing, Salt Lake City, April 2008
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