Especialmente por se tratar de uma ´area de pesquisa relativamente nova, praticamente tudo relacionado direta ou indiretamente e a UTM ´e um potencial trabalho futuro. Em se
tratando do escopo desse trabalho, podem ser considerados como frentes de continuidade:
• levar em considera¸c˜ao, no escopo da simula¸c˜ao de portadora, o tempo entre en- vio de mensagens e modos de falha espec´ıficos ao processo de envio e recebimento de mensagens (por exemplo, mensagem corrompida, falha em solicitar reenvio de mensagem, dentre outros);
• especificar o comportamento do VANT em caso de emergˆencia (que justificasse, por exemplo, o envio de uma mensagem do tipo DISTRESS ao espa¸co a´ereo, conforme mencionado em 6.1.2);
• implementar o envio e interpreta¸c˜ao de mensagens em modo an´alogo ao de r´adio- difus˜ao, com finalidade de estabelecimento de comunica¸c˜ao entre uma entidade cen- tral e os VANTs presentes em um espa¸co a´ereo. Uma poss´ıvel aplica¸c˜ao dessa funcionalidade seria, por exemplo, fechar o espa¸co a´ereo e anunciar pontos onde eventuais VANTs presentes pousassem (situa¸c˜ao an´aloga a ocorrida durante o 11 de setembro);
• considerar um evento de risco onde um VANT que n˜ao esteja em adequa¸c˜ao com os procedimentos e padr˜oes operacionais do espa¸co a´ereo (e.g. sem transmitir sua posi¸c˜ao pelo enlace de comunica¸c˜ao padr˜ao) adentre no espa¸co a´ereo;
• considerar procedimentos relacionadoas a decolagem e pouso (nomeados em UTM como last 50ft, ´ultimos 50 p´es em uma tradu¸c˜ao livre para o portuguˆes);
• considerar processo de preven¸c˜ao de colis˜ao ”intracelular”(quando dois VANTs se encontrem em uma mesma c´elula);
• desenvolvimento de metodologia para ”projeto”do espa¸co a´ereo, envolvendo o di- mensionamento de c´elulas e demarca¸c˜ao de obst´aculos.
• condu¸c˜ao de estudos sobre a capacidade de uso do espa¸co a´ereo decorrente da uti- liza¸c˜ao do algoritmo proposto nesse documento, em conjunto com a avalia¸c˜ao de eventuais eventos de risco associados.
REFERˆENCIAS
1 BBC. Drone causes Gatwick Airport interruption. 2017. Dispon´ıvel em: hhttp: //www.bbc.com/news/uk-40476264i. Acesso em: 24-01-2018.
2 NASA. Global Positioning System History. 2012. Dispon´ıvel em: hhttps:
//www.nasa.gov/directorates/heo/scan/communications/policy/GPS\ History.htmli. Acesso em: 03-03-2018.
3 CODE7700. CPDLC Communications. 2017. Dispon´ıvel em: hhttp://code7700.com/ communications\ cpdlc.htmi. Acesso em: 28-03-2018.
4 STROHMEIER, M.; LENDERS, V.; MARTINOVIC, I. Security of ADS- B: state of the art and beyond. CoRR, abs/1307.3664, 2013. Dispon´ıvel em: hhttp://arxiv.org/abs/1307.3664i.
5 ICAO. Global Air Navigation Plan for CNS/ATM Systems. 2002. Dispon´ıvel em: hhttps://www.icao.int/publications/Documents/9750\ 2ed\ en.pdfi. Acesso em: 30-04-2018.
6 FAA. Concept of Operations - Unmanned Aircraft System (UAS) Traffic Management (UTM). v1.0. Washington, D.C.: FAA, 2018. 52 p.
7 DEBS, C. Game of Life. 2015. Dispon´ıvel em: hhttp://web.stanford.edu/{∼}cdebs/
GameOfLifi. Acesso em: 2018-03-14.
8 TERO, A. et al. Rules for Biologically Inspired Adaptive Network Design. Science, v. 327, n. 5964, 2010.
9 PREVOT, T. et al. Uas traffic management (utm) concept of operations to safely enable low altitude flight operations. In: 16th AIAA Aviation Technology, Integration, and Operations Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. ISBN 978-1-62410-440-4. Dispon´ıvel em: hhttp://arc.aiaa.org/doi/10.2514/6.2016-3292i.
10 GIMENES, R. A. et al. Guidelines for the integration of autonomous uas into the global atm. Journal of Intelligent and Robotic Systems: Theory and Applications, v. 74, n. 1-2, 2014. ISSN 09210296.
11 KAMIENSKI, J.; SEMANEK, J. Atc perspectives of uas integration in controlled airspace. Procedia Manufacturing, v. 3, 2015. ISSN 23519789.
12 RAMASAMY R. SABATINI, A. G. S. A unified approach to separation assurance and collision avoidance for uas operations and traffic management. In: IEEE.
International Conference on Unmanned Aircraft Systems (ICUAS 2017) - Miami, FL, USA. [S.l.], 2017.
13 FURTADO, V. H. et al. Aspectos de seguran¸ca na integra¸c˜ao de ve´ıculos a´ereos n˜ao tripulados (vant) no espa¸co a´ereo brasileiro. Sitraer, v. 7, p. 12, 2008.
14 TELEGRAPH. Defibrillator drones to boost cardiac arrest survival. 2017. Dispon´ıvel em: hhttp://www.telegraph.co.uk/science/2017/06/13/ defibrillator-drones-boost-cardiac-arrest-survival/i. Acesso em: 26-06-2017. 15 GUARDIAN, T. Amazon claims first successful Prime Air drone delivery. 2016. Dispon´ıvel em: hhttps://www.theguardian.com/technology/2016/dec/14/ amazon-claims-first-successful-prime-air-drone-deliveryi. Acesso em: 24-01-2018. 16 CNET. Amazon Prime Air drone completes its first US public de- livery - CNET. 2017. Dispon´ıvel em: hhttps://www.cnet.com/news/
amazon-prime-air-first-drone-delivery-us-public-sunscreen-mars/i. Acesso em: 24-01-2018.
17 RURAL, G. 15 usos de drones na agricultura e na pecu´aria - Globo Rural. 2015. Dispon´ıvel em: hhttp://revistagloborural.globo.com/Noticias/Pesquisa-e-Tecnologia/ noticia/2015/05/15-usos-de-drones-na-agricultura-e-na-pecuaria.htmli. Acesso em: 24-01-2018.
18 G1. Cresce o mercado de drones para agricultura em Mato Grosso. 2017. Dispon´ıvel em: hhttps://g1.globo.com/mt/mato-grosso/noticia/
cresce-o-mercado-de-drones-para-agricultura-em-mato-grosso.ghtmli. Acesso em: 24-01-2018.
19 PROTECTION, E. C.; OPERATIONS, H. A. How Drones Can Help in Humanitarian Crises - European Commission. Dispon´ıvel em: hhttp://ec.europa.eu/ echo/field-blogs/stories/how-drones-can-help-humanitarian-crises\ eni. Acesso em: 2017-06-26.
20 EXAME.COM. Drone vira arma da Pol´ıcia Federal contra o crime no Rio. 21 COMPANY, M. . Commercial drones are here: The future
of unmanned aerial systems. 2017. Dispon´ıvel em: hhttps://www. mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/
commercial-drones-are-here-the-future-of-unmanned-aerial-systemsi. Acesso em: 24-01-2018.
22 BAYAR, T. How drones are playing a role in the power and utility sector. 2018. Dispon´ıvel em: hhttp://www.powerengineeringint.com/articles/2018/02/ how-drones-are-playing-a-role-in-the-power-and-utility-sector.htmli. Acesso em: 07-03-2018.
23 REUTERS. Embraer sees 2024 commercial launch for Uber flying cabs. 2017. Dispon´ıvel em: hhttps://www.reuters.com/article/us-embraer-outlook-uber/ embraer-sees-2024-commercial-launch-for-uber-flying-cabs-idUSKBN1E929Ni. Acesso em: 07-03-2018.
24 WIRED. Airbus Swears Its Pod/Car/Drone Is a Serious Idea Definitely. 2017. Dispon´ıvel em: hhttps://www.wired.com/2017/03/ airbus-swears-podcardrone-serious-idea-definitely/i. Acesso em: 07-03-2018.
25 DECEA. ICA 100-40 - Sistemas de Aeronaves Remotamente Pi- lotadas e o Acesso ao Espa¸co A´ereo Brasileiro (10.03.2017). 2017. Https://publicacoes.decea.gov.br/?i=publicacao&id=4510. Dispon´ıvel em:
hhttps://publicacoes.decea.gov.br/?i=publicacao{\&}id=4i. Acesso em: 24-01-2018. 26 G1. Drone sobre Congonhas pode causar preju´ızo de mais
de 1 milh˜ao de reais, estima associa¸c˜ao de empresas a´ereas. 2017. Dispon´ıvel em: hhttps://g1.globo.com/sao-paulo/noticia/
drone-sobre-congonhas-causou-prejuizo-de-mais-de-r-1-milhao-estima-associacao. ghtmli. Acesso em: 09-03-2018.
27 SHEPARDSON, D. Drone operator caused U.S. Army helicopter collision: safety board. 2017. Dispon´ıvel em: hhttps://www.reuters.com/article/us-usa-military-drone/ drone-operator-caused-u-s-army-helicopter-collision-safety-board-idUSKBN1E82EGi. Acesso em: 09-03-2018.
28 RESEARCH, N. I. for A. Dot/faa/ar-xx/xx uas airborne colli- sion severity evaluation executive summary – structural evaluation. 2017. Dispon´ıvel em: hhttp://www.assureuas.org/projects/deliverables/a3/ VolumeI-UASAirborneCollisionSeverityEvaluation-StructuralEvaluation.pdfi. 29 GSA-EU. What is Galileo? 2018. Dispon´ıvel em: hhttps://www.gsa.europa. eu/european-gnss/galileo/galileo-european-global-satellite-based-navigation-systemi. Acesso em: 03-03-2018.
30 IAC-RU. GLONASS history. 200? Dispon´ıvel em: hhttps://www.glonass-iac.ru/en/ guide/index.phpi. Acesso em: 03-03-2018.
31 HOFMANN-WELLENHOF, B.; LICHTENEGGER, H.; WASLE, E. GNSS–global navigation satellite systems: GPS, GLONASS, Galileo, and more. [S.l.]: Springer Science & Business Media, 2007.
32 SESSO, D. B. Avalia¸c˜ao de seguran¸ca em sistemas de controle de tr´afego a´ereo baseados em vigilˆancia dependente autom´atica por radiodifus˜ao considerando parˆametros de integridade de dados.
33 DJI. D-RTK GNSS - Specs - DJI. 2017. Dispon´ıvel em: hhttps://www.dji.com/ d-rtk/infoi. Acesso em: 22-02-2018.
34 SWIFTNAV. RTK UAV, Autonomous Vehicle Navigation, Orthomosaics, Precision Agriculture, Centimeter Accuracy GPS, Global Navigation Satellite System, Real-Time Kinematics, High-Precision GPS, Unmanned Aerial Vehicles, Swift Binary Protocol — SwiftNav. 2018. Dispon´ıvel em: hhttps://www.swiftnav.com/uavi. Acesso em: 22-02-2018.
35 ATLAVIAN. Why use PPK with your drone (not RTK) - Altavian Inc. 2016. Dispon´ıvel em: hhttps://www.altavian.com/knowledge-base/use-ppk-drone-not-rtk/i. Acesso em: 22-02-2018.
36 NOAA. National geodetic survey - cors homepage. 2017. Dispon´ıvel em: hhttps://www.ngs.noaa.gov/CORS/i.
37 GILHOLLY, R. Entering the drone age: Japan seeks to tap into the potential of unmanned flying vehicles. 2018. Dispon´ıvel em: hhttps://www.japantimes.co.jp/life/2018/ 01/20/digital/entering-drone-age-japan-seeks-tap-potential-unmanned-flying-vehicles/ \#.Wprv9Xdv\ IUi. Acesso em: 03-03-2018.
38 DOHERTY, P. H. et al. Ionospheric effects on aviation applications in South America. In: 2014 XXXIth URSI General Assembly and Scientific Symposium (URSI GASS). IEEE, 2014. p. 1–1. ISBN 978-1-4673-5225-3. Dispon´ıvel em: hhttp://ieeexplore.ieee.org/document/6929724/i.
39 VISMARI, L. F. Vigilˆancia dependente autom´atica no controle de tr´afego a´ereo: avalia¸c˜ao de risco baseada em modelagem em redes de Petri fluidas e estoc´asticas. Disserta¸c˜ao (Mestrado) — Universidade de S˜ao Paulo, 2007.
40 ICAO. Annex 11 - air traffic services. Montreal, Canada: International Civil Aviation Organization, 2001.
41 AERON ´AUTICA, C. da. Departamento de controle do espa¸co a´ereo–decea (2001). ICA 100-12, Regras do Ar e Servi¸cos de Tr´afego A´ereo, 2007.
42 DECEA. Ica 100-38, espa¸co a´ereo condicionado. 2017.
43 SHORROCK, S. T. Errors of perception in air traffic control. Safety Science, v. 45, n. 8, p. 890–904, oct 2007. ISSN 09257535. Dispon´ıvel em: hhttp://www.sciencedirect. com/science/article/pii/S0925753506001056i.
44 DECEA. MCA 100-16, Fraseologia de Tr´afego A´ereo, 2016.
45 SHORROCK, S. T. Errors of memory in air traffic control. Safety Science, v. 43, n. 8, p. 571–588, oct 2005. ISSN 09257535. Dispon´ıvel em: hhttp://www.sciencedirect. com/science/article/pii/S0925753505000664i.
46 ANAC. Rbha 91 - regras gerais de opera¸c˜ao para aeronaves civis. 2011. Acesso em: 23-03-2018.
47 ICAO. Doc 4444-Procedures for Air Navigation Services Air Traffic Management. [S.l.]: International Civil Aviation Organization Montr´eal, 2007.
48 FAA. Data communications implementation team tower data link services controller pilot data link communication departure clearance service (cpdlc-dcl) flight deck user guide. 2016. Dispon´ıvel em: hhttps://www.faa.gov/about/office\ org/headquarters\
offices/avs/offices/afx/afs/afs400/afs470/datacomm/media/DCL\ FDUG.pdfi. 49 GIL, F. d. O. Metodologia de avalia¸c˜ao de seguran¸ca das comunica¸c˜oes entre controlador e piloto via enlace de dados (CPDLC) aplicada em ´areas terminais. 2011. 50 DECEA. DECEA conclui infraestrutura para operar ADS-B na Bacia de Campos. 2015. Dispon´ıvel em: hhttps://www.decea.gov.br/sirius/index.php/2015/09/04/ decea-conclui-infraestrutura-para-operar-ads-b-na-bacia-de-campos-4/i. Acesso em: 24-04-2018.
51 AUSTRALIA, A. This is a test entry of type @ONLINE. 2017. Dispon´ıvel em: hhttp://www.airservicesaustralia.com/projects/ads-b/upper-airspace-mandate-2013/i. Acesso em: 24-04-2018.
52 CENIPA. Relat´orio Final A-022/CENIPA/2008. 2008. 53 CENIPA. Relat´orio final a-134/cenipa/2014. 2014.
54 (BFU), B. f¨ur F. Ax001-1-2/02 may 2004. p. 1–116, 2004. Dispon´ıvel em: hhttps: //www.bfu-web.de/EN/Publications/Investigation\%20Report/reports\ node.htmli. 55 ANAC. Rbac 135 - requisitos operacionais: Opera¸c˜oes complementares e por demanda. 2014.
56 MELNYK, R. et al. A third-party casualty risk model for unmanned aircraft system operations. Reliability Engineering and System Safety, v. 124, 2014. ISSN 09518320. 57 MELNYK, R. et al. Sense and avoid requirements for unmanned aircraft systems using a target level of safety approach. Risk Analysis, v. 34, n. 10, 2014. ISSN 15396924. 58 GAGEIK, N.; BENZ, P.; MONTENEGRO, S. Obstacle detection and collision avoidance for a UAV with complementary low-cost sensors. IEEE Access, v. 3, 2015. ISSN 21693536.
59 JENIE, Y. I. et al. Conflict Detection and Resolution System Architecture for Unmanned Aerial Vehicles in Civil Airspace. In: AIAA Infotech @ Aerospace. [S.l.: s.n.], 2015. ISBN 978-1-62410-338-4.
60 BRASILEIRA, F. A. Tr´afego A´ereo - Entenda o conceito CNS/ATM. 2011. Dispon´ıvel em: hhttp://www.fab.mil.br/noticias/mostra/8543/TR\%C3\%81FEGO-A\ %C3\%89REO---Entenda-o-conceito-CNS/ATM-\%28Perguntas-Frequentes\%29i. Acesso em: 30-04-2018.
61 NAUGHTON, R. The first air raid - by balloons! 2003. Dispon´ıvel em: hhttp://www.ctie.monash.edu/hargrave/rpav\ home.html\#Beginningsi. Acesso em: 01-05-2018.
62 INSIDER, B. A history fo commercial drones. 2016. Dispon´ıvel em: hhttp: //www.businessinsider.com/a-history-of-commercial-drones-2016-12i. Acesso em: 01-05-2018.
63 MUSEUM, I. W. A brief history of drones. 2018. Dispon´ıvel em: hhttps: //www.iwm.org.uk/history/a-brief-history-of-dronesi. Acesso em: 01-05-2018. 64 HOVERSTEN, P. Were drones used in the Bikini bomb tests?
2013. Dispon´ıvel em: hhttps://www.airspacemag.com/need-to-know/
were-drones-used-in-the-bikini-bomb-tests-6578388/i. Acesso em: 02-05-2018. 65 AIR, S. N.; MUSEUM, S. UAV, General Atomics MQ-1L Preda- tor A. 2016. Dispon´ıvel em: hhttps://airandspace.si.edu/collection-objects/ uav-general-atomics-mq-1l-predatori. Acesso em: 02-05-2018.
66 AEROVIRONMENT. AeroVironment’s Pathfinder Solar Unmanned Aircraft Lands in Smithsonian Institution. 2007. Dispon´ıvel em: hhttp://investor.avinc.com/ releasedetail.cfm?releaseid=439895i. Acesso em: 02-05-2018.
67 PE ˜NA, N.; SCARLATTI, D.; OLLERO, A. Uavs integration in the swim based architecture for atm. In: . Unmanned Aircraft Systems: International Symposium On Unmanned Aerial Vehicles, UAV’08. Dordrecht: Springer Netherlands, 2009. p. 39–59. ISBN 978-1-4020-9137-7. Dispon´ıvel em: hhttps://doi.org/10.1007/ 978-1-4020-9137-7\ 4i.
68 KOPARDEKAR, P. H. Unmanned aerial system (uas) traffic management (utm): Enabling low-altitude airspace and uas operations (nasa/tm—2014–218299). 2014. 69 WANG, X.; YADAV, V.; BALAKRISHNAN, S. Cooperative uav formation flying with obstacle/collision avoidance. IEEE Transactions on control systems technology, IEEE, v. 15, n. 4, p. 672–679, 2007.
70 CHANG, D. E. et al. Collision avoidance for multiple agent systems. In: 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475). [S.l.: s.n.], 2003. v. 1, p. 539–543 Vol.1. ISSN 0191-2216.
71 LOZANO-P´EREZ, T.; WESLEY, M. A. An algorithm for planning collision-free paths among polyhedral obstacles. Communications of the ACM, ACM, v. 22, n. 10, p. 560–570, 1979.
72 ZHANG, Y. et al. Decentralized cooperative trajectory planning for multiple UAVs in dynamic and uncertain environments. In: 2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS). IEEE, 2015. p. 377–382. ISBN 978-1-5090-1949-6. Dispon´ıvel em: hhttp://ieeexplore.ieee.org/lpdocs/ epic03/wrapper.htm?arnumber=7397248i.
73 HAN, S.-C.; BANG, H. Proportional navigation-based optimal collision avoidance for uavs. In: 2nd International Conference on Autonomous Robots and Agents. [S.l.: s.n.], 2004. p. 13–15.
74 KOSECKA, J. et al. Generation of conflict resolution manoeuvres for air traffic management. In: IEEE. Intelligent Robots and Systems, 1997. IROS’97., Proceedings of the 1997 IEEE/RSJ International Conference on. [S.l.], 1997. v. 3, p. 1598–1603.
75 RAMASAMY R. SABATINI, A. G. S. A unified approach to separation assurance and collision avoidance for uas operations and traffic management. In: IEEE.
International Conference on Unmanned Aircraft Systems (ICUAS 2017) - Miami, FL, USA. [S.l.], 2017.
76 KIM, K.-Y.; PARK, J.-W.; TAHK, M.-J. Uav collision avoidance using probabilistic method in 3-d. In: IEEE. Control, Automation and Systems, 2007. ICCAS’07.
International Conference on. [S.l.], 2007. p. 826–829.
77 WOLFRAM, S. Statistical mechanics of cellular automata. Reviews of modern physics, APS, v. 55, n. 3, p. 601, 1983.
78 Hern´andez Encinas, L. et al. Modelling forest fire spread using hexagonal cellular automata. Applied Mathematical Modelling, v. 31, n. 6, p. 1213–1227, 2007. ISSN 0307904X. Dispon´ıvel em: hhttp://www.sciencedirect.com/science/article/pii/ S0307904X06000916i.
79 TRUNFIO, G. A. Predicting Wildfire Spreading Through a Hexagonal Cellular Automata Model. In: . [S.l.: s.n.], 2004. ISBN 978-3-540-23596-5.
80 WOLFRAM, S. Random sequence generation by cellular automata. Advances in Applied Mathematics, v. 7, n. 2, p. 123–169, jun 1986. ISSN 01968858. Dispon´ıvel em: hhttp://linkinghub.elsevier.com/retrieve/pii/019688588690028Xi.
81 NANDI, S.; KAR, B. K.; CHAUDHURI, P. P. Theory and applications of cellular automata in cryptography. IEEE Transactions on Computers, v. 43, n. 12, p. 1346–1357, Dec 1994. ISSN 0018-9340.
82 AL-SHALABI, M. et al. Modelling urban growth evolution and land-use changes using gis based cellular automata and sleuth models: the case of sana’a metropolitan city, yemen. Environmental earth sciences, Springer, v. 70, n. 1, p. 425–437, 2013. 83 KAUFFMANN, C.; PICH´E, N. Seeded nd medical image segmentation by cellular automaton on gpu. International journal of computer assisted radiology and surgery, Springer, v. 5, n. 3, p. 251–262, 2010.
84 SCHIFF, J. L. Cellular Automata: A Discrete View of the World (Google eBook). Wiley-Interscience, 2011. 252 p. ISBN 111803063X. Dispon´ıvel em: hhttp://books.google.com/books?hl=de&lr=&id=uXJC2C2sRbIC&pgis=1i.
85 TZIONAS, P.; THANAILAKIS, A.; TSALIDES, P. Collision-free path planning for a diamond-shaped robot using two-dimensional cellular automata. IEEE Transactions on Robotics and Automation, v. 13, n. 2, p. 237–250, apr 1997. ISSN 1042296X. Dispon´ıvel em: hhttp://ieeexplore.ieee.org/document/563646/i.
86 SYED, U. A.; KUNWAR, F. Cellular automata based real-time path-planning for mobile robots. International Journal of Advanced Robotic Systems, SAGE PublicationsSage UK: London, England, v. 11, n. 7, p. 93, jul 2014. ISSN 1729-8814. Dispon´ıvel em: hhttp://journals.sagepub.com/doi/10.5772/58544i.
87 SOOFIYANI, F. R.; RAHMANI, A. M.; MOHSENZADEH, M. A straight moving path planner for mobile robots in static environments using cellular automata. In: 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks. IEEE, 2010. p. 67–71. ISBN 978-1-4244-7837-8. Dispon´ıvel em: hhttp://ieeexplore.ieee.org/document/5614583/i.
88 MARCHESE, F. M. A directional diffusion algorithm on cellular automata for robot path-planning. Future Generation Computer Systems, North-Holland, v. 18, n. 7, p. 983–994, aug 2002. ISSN 0167-739X. Dispon´ıvel em: hhttp://www.sciencedirect.com. focus.lib.kth.se/science/article/pii/S0167739X02000778?via\%3Dihubi.
89 MARCHESE, F. M. Multiple mobile robots path-planning with mca. In:
International Conference on Autonomic and Autonomous Systems (ICAS’06). [S.l.: s.n.], 2006. p. 56. ISSN 2168-1864.
90 AKBARIMAJD, A.; HASSANZADEH, A. Autonomously implemented versatile path planning for mobile robots based on cellular automata and ant colony. International Journal of Computational Intelligence Systems, v. 5, n. 1, p. 39–52, feb 2012. ISSN 1875-6891. Dispon´ıvel em: hhttp://www.atlantis-press.com/php/paper-details.php?id= 25867957i.
91 TAVAKOLI, Y.; JAVADI, H.; ADABI, S. A cellular automata based algorithm for path planning in multi-agent systems with a common goal. International journal of, 2008. Dispon´ıvel em: hhttps://www.researchgate.net/profile/Hamid\ Haj\ Seyyed\
Javadi/publication/255063848\ A\ Cellular\ Automata\ Based\ Algorithm\ for\ Path\ Planning\ in\ Multi-Agent\ Systems\ with\ A\ Common\ Goal/links/ 0046353b58ad4850f7000000.pdfi.
92 BEHRING, C. et al. An Algorithm for Robot Path Planning with Cellular Automata. In: Theory and Practical Issues on Cellular Automata. London: Springer London, 2001. p. 11–19. Dispon´ıvel em: hhttp://link.springer.com/10.1007/978-1-4471-0709-5\ 2i. 93 TSOMPANAS, M.-A. I.; SIRAKOULIS, G. C. Modeling and hardware
implementation of an amoeba-like cellular automaton. Bioinspiration & Biomimetics, IOP Publishing, v. 7, n. 3, p. 036013, sep 2012. ISSN 1748-3182. Dispon´ıvel em: hhttp://stacks. iop.org/1748-3190/7/i=3/a=036013?key=crossref.f251c221003f2323ed207876484dfb6bi. 94 Eurocontrol Experimental Centre. Bada user manual. n. 3.7, 2009.
APˆENDICE A – LISTA DE CASOS DE
USO
A.1
Criar Cen´ario
Evento iniciador:Usu´ario clica na op¸c˜ao Atores:Usu´ario
Pr´e-condi¸c˜ao:Usu´ario encontra-se no menu principal (ver prot´otipo de interface ”Create a New Scenario”na figura 25).
Sequˆencia de eventos:
1. Usu´ario entra com a largura do reticulado, em metros.
2. Usu´ario entra com a altura do reticulado, em metros.
3. Usu´ario entra com o lado da c´elula, em metros (no caso, corresponde a aresta do hex´agono).
4. Usu´ario entra com a velocidade a ser adotada pelo UAV (em metros por segundo).
5. Usu´ario entra com a velocidade de simula¸c˜ao, em passos (ticks) por segundo.
6. Usu´ario marca se deseja considerar a degrada¸c˜ao de performance no cen´ario em quest˜ao.
7. Usu´ario configura a entrada de degrada¸c˜ao de GNSS.
8. Usu´ario configura a entrada de degrada¸c˜ao de taxa de erros de mensagem.
9. Usu´ario configura a entrada de degrada¸c˜ao de tempo total de resposta.