NEST Introduction
Network of Electronic Self-Navigating TransportsSean Buckley, Varatep Buranintu, Dragos Guta, Jeffrey LimbacherYun Kim, Pinar Sayim, David WuMay 8th, 2015, COMP 491 Senior Design, CSUN Department of Computer Science Customer: Dr. Ho, Systems Engineering Research Laboratory
SYSTEMS ENGINEERINGRESEARCH LABORATORY
AgendaMotivation and Vision StatementGoals and AssumptionsDevelopment ProcessConclusionsAcknowledgementsReferencesSystems Engineering Research Laboratory1
MotivationGrowing interest in dronesMany different practical applicationsGoogle Wings and Amazon Prime AirCustomer: Dr. Ho wants large scale unmanned aircraft system (UAS) test bedSystems Engineering Research Laboratory2
UAS ChallengesSafetyAvoiding peopleAvoiding obstaclesManaging a large fleetHandling off-nominal situationsProviding pertinent information to operatorsOperator-automation interactionSystems Engineering Research Laboratory3
Vision StatementGiven thatUAS automation will enable fully autonomous flightHumans must be able to intervene in off-nominal situationsCurrent control systems are not viableNEST willFill the gapProvide automation and tools for operatorsAllow a small group to manage a large set of vehiclesSystems Engineering Research Laboratory4
Goals
Systems Engineering Research Laboratory5
SYSTEMS ENGINEERINGRESEARCH LABORATORY
NEST Team GoalsDevelop an independent Air Operations Control (AOC) Center for unmanned air vehicles (UAVs)Manage upwards of 500 to 1000 UAVs in a 10 mile radius with 1 to 10 operatorsProvide operators with UAV detailsAbility to give navigational commands to UAVsDesign an experiment to evaluate our solutionConstruct a working prototype by using software development process learned in COMP 380/490Systems Engineering Research Laboratory6
Requirements ResearchSimilar SystemsAir Operations CentersDispatch SystemsResearch broken into domains for areas of interestNASA & Military AOCs, LGDs, maps with overlays, multiple displays at oncePsychology managing large number of thingsGaming Information displays, unit controlCommercial Vehicle monitoring, schedulingMeeting with customerSystems Engineering Research Laboratory7
AssumptionsFAARegulations freely permit commercial UAV flightsFlight of UAVs over medium- to highly-populated areas allowedIntegration of commercial UAV into National Airspace System (NAS)Highly automated UAVsObject avoidanceGround avoidanceCourse correctionSystems Engineering Research Laboratory8
Development Process
Systems Engineering Research Laboratory9
SYSTEMS ENGINEERINGRESEARCH LABORATORY
Project TimelineSystems Engineering Research Laboratory10
Technology choicesMicrosofts ASP.NET MVC using C# (Visual Studio)SignalRHTML, JavaScript, CSSAngularJSGoogle MapsSystems Engineering Research Laboratory11
.net mvc makes it easier to divide complexity..net because well-supported, solid community, and powerful librariesSignalR easily added with visual studios package manager. deliver communication between client and server in both directions bidirectionally and simultaneously.i.e. two websocket frame bytes can replace hundreds of HTTP header bytesHTML/JS/CSS because its a web applicationAngularJS allows us to create highly interactive client-side codeGoogle maps - as our mapping solution because of its well documented api11
Team Member Roles and ResponsibilitiesSystems Engineering Research Laboratory12
Core of front endmap viewmain contributors: david, seanrest of us helped where necessaryCore of back endrest apis and simulationmain contributors: varatep, dragosjeff
12
Development ProcessScrumOne week sprintsGather user stories from customer, Dr. HoPopulate backlogAssign tasksContinuous IntegrationMeetings with industry professionalsTeam Bonding
Systems Engineering Research Laboratory13
Scrumwhat we did yesterdaywhat we plan on doing todayblockersScrum master = jeff
Cont int: to ensure project stability, we used continuous integration. We used travis ci, an external testing application, to automate our build testing
Mention that we met with dr. ho to ensure that we are on track and to gather new tasks and requirementsalso demo to dr hoTalk with industry professionals to reaffirm our requirements and assumptions and for their domain knowledgealso demo to an industry professional
Team bondingengaged teammates13
Sprint WorkflowSystems Engineering Research Laboratory14
Tangible = small and specific tasks that are doable within the sprint scope instead of large abstract tasksthis way not multitasking, which can kill efficiency
Sprint review -> critique each other14
Project Management and ToolsCommunicationSlackSkypeContent SharingGoogle DriveSource ControlAtlassian SourceTree GithubProject ManagementJIRAMockupsBalsamiqSystems Engineering Research Laboratory15
Never gathered each others phone numbers15
Example Burn Down ChartSystems Engineering Research Laboratory16
How we tracked our progress
16
Systems Engineering Research Laboratory17
Systems Engineering Research Laboratory18
DemoSystems Engineering Research Laboratory19
ExperimentGoalsA total of 3 operators running through the softwareThe experiment was between two trials:50 UAVs and 100 UAVsNASA Task Load Index assessed the overall workload of the operators for bothResultsParticipants found value in all the displaysParticipants were able to address problems However, addressing problems took too much timeSystems Engineering Research Laboratory20
Conclusion
Systems Engineering Research Laboratory21
SYSTEMS ENGINEERINGRESEARCH LABORATORY
What We AccomplishedCommand and Control of vehiclesMultiple displays for providing information to the operatorMap displays vehicle position and birds eye view of the operational areaDisplay for vehicle-specific informationShow delivery statusDisplays support showing large amounts of UAVsEvents bring operator attention to issuesSystem for UAV assignment based on contingency events
Systems Engineering Research Laboratory22
Future WorkLook into operators influence in safetyReactive system versus predictive systemWhat automation will realistically be in the aircraft or systemHow does this influence how the operator interacts with the rest of the systemWhat information to present to the operatorInformation is context sensitive
Systems Engineering Research Laboratory23
ConclusionsControlling and monitoring a large number of UAVs is feasibleThere are many technical issues that need to be addressedWhat in the system is automated and to what degreeSpend more time on designImportant to adapt the process to the teamChanged sprint length and created subgroups
Systems Engineering Research Laboratory24
What We LearnedSpend more time on system designCommunication is keyImportant to adapt the process to the teamChanged sprint length and created subgroupsShared knowledge over specialists
Systems Engineering Research Laboratory25
Comparing Semester One and TwoSemester 1
Semester 2
Systems Engineering Research Laboratory26
AcknowledgementsDr. Nhut Ho CSUN, Mechanical Engineering, CustomerDr. Walter Johnson NASA Ames Research Center, Human Systems IntegrationCody Evans Airline Operations DispatcherSystems Engineering Research Laboratory27
ReferencesAmazon Prime Air, http://www.amazon.com/b?node=80377200114Drone Industry Expected to Grow to $11 Billion by 2024, http://www.livescience.com/47071-drone-industry-spending-report.htmlFAA Unmanned Aircraft Systems, https://www.faa.gov/uas/NASA Unmanned Aerial System Traffic Management (UTM), http://www.aviationsystemsdivision.arc.nasa.gov/utm/index.shtml
Systems Engineering Research Laboratory28
Questions
Systems Engineering Research Laboratory29
SYSTEMS ENGINEERINGRESEARCH LABORATORY