Multiple UAVs for Mapping: A Review of Basic Modeling, Simulation, and Applications

Literature Cited

1. 1.  Totaro P, Kakaes K 2016. Whose sky is it anyway? U.S. drone case tests rights to air space. Reuters Sep. 21. https://www.reuters.com/article/us-property-drones-rights/whose-sky-is-it-anyway-u-s-drone-case-tests-rights-to-air-space-idUSKCN11R1ND
2. 2.  Zohdi TI 2017. On the dynamics and breakup of quadcopters using a discrete element method framework. Comput. Methods Appl. Mech. Eng. 327:503–21
   [Google Scholar]
3. 3.  Breder CM 1954. Equations descriptive of fish schools and other animal aggregations. Ecology 35:3361–70
   [Google Scholar]
4. 4.  Gazi V, Passino KM 2002. Stability analysis of swarms. Proceedings of the 2002 American Control Conference, May 8–10, Hilton Anchorage and Egan Convention Center, Anchorage, AK 31813–18 Piscataway, NJ: IEEE
   [Google Scholar]
5. 5.  Bender J, Fenton R 1970. On the flow capacity of automated highways. Transport Sci 4:52–63
   [Google Scholar]
6. 6.  Kennedy J, Eberhart R 2001. Swarm Intelligence San Francisco: Morgan Kaufmann
7. 7.  Zohdi TI 2003. Computational design of swarms. Int. J. Numer. Methods Eng. 57:2205–19
   [Google Scholar]
8. 8.  Zohdi TI 2009. Mechanistic modeling of swarms. Comput. Methods Appl. Mech. Eng. 198:21–262039–51
   [Google Scholar]
9. 9.  Zohdi TI 2017. An agent-based computational framework for simulation of competing hostile planet-wide populations. Comput. Methods Appl. Mech. Eng. 314:513–26
   [Google Scholar]
10. 10.  Beni G 1988. The concept of cellular robotic system. Proceedings: IEEE International Symposium on Intelligent Control 1988, Aug. 24–26, Arlington, VA HE Stephanou, A Meystel, JYS Luh 57–62 Piscataway, NJ: IEEE
    [Google Scholar]
11. 11.  Brooks RA 1991. Intelligence without reason. Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI-91), Aug. 24–30 1 J Mylopoulos, R Reiter 569–95 San Francisco: Morgan Kaufmann
    [Google Scholar]
12. 12.  Dudek G, Jenkin M, Milios E, Wilkes D 1996. A taxonomy for multi-agent robotics. Auton. Robots 3:375–97
    [Google Scholar]
13. 13.  Cao YU, Fukunaga AS, Kahng A 1997. Cooperative mobile robotics: antecedents and directions. Auton. Robots 4:17–27
    [Google Scholar]
14. 14.  Liu Y, Passino KM 2000. Swarm intelligence: literature overview Tech. Rep. Ohio State Univ.
15. 15.  Bonabeau E, Dorigo M, Theraulaz G 1999. Swarm Intelligence: From Natural to Artificial Systems New York: Oxford Univ. Press
16. 16.  Dorigo M, Maniezzo V, Colorni A 1996. Ant system: optimization by a colony of cooperating agents. IEEE Trans. Syst. Man Cybern. B 26:129–41
    [Google Scholar]
17. 17.  Bonabeau E, Meyer C 2001. Swarm intelligence: a whole new way to think about business. Harvard Bus. Rev. 79:5106–14
    [Google Scholar]
18. 18.  Fiorelli E, Leonard NE, Bhatta P, Paley D, Bachmayer R, Fratantoni DM 2004. Multi-AUV control and adaptive sampling in Monterey Bay. 2004 IEEE/OES Autonomous Underwater Vehicles, June 17–18, Sebasco, ME134–47 Piscataway, NJ: IEEE
    [Google Scholar]
19. 19.  Feder T 2007. Statistical physics is for the birds. Phys. Today. 60:1028
    [Google Scholar]
20. 20.  Ballerini M, Cabibbo N, Candelier R, Cavagna A, Cisbani E et al. 2008. Interaction ruling animal collective behavior depends on topological rather than metric distance: evidence from a field study. PNAS 105:41232–37
    [Google Scholar]
21. 21.  Haile JM 1992. Molecular Dynamics Simulations: Elementary Methods New York: Wiley
22. 22.  Zohdi TI 2002. An adaptive-recursive staggering strategy for simulating multifield coupled processes in microheterogeneous solids. Int. J. Numer. Methods Eng. 53:1511–32
    [Google Scholar]
23. 23.  Zohdi TI 2004. Modeling and simulation of a class of coupled thermo-chemo-mechanical processes in multiphase solids. Comput. Methods Appl. Mech. Eng. 193:6–8679–99
    [Google Scholar]
24. 24.  Zohdi TI, Wriggers P 2008. Introduction to Computational Micromechanics Berlin: Springer
25. 25.  Zohdi TI 2010. Simulation of coupled microscale multiphysical-fields in particulate-doped dielectrics with staggered adaptive FDTD. Comput. Methods Appl. Mech. Eng. 199:79–101
    [Google Scholar]
26. 26.  Hedrick JK, Swaroop D 1993. Dynamic coupling in vehicles under automatic control. The Dynamics of Vehicles on Roads and on Tracks. Proceedings of the 13th IAVSD Symposium, Aug. 23–27, Chengdu, Sichuan, China209–20 Amsterdam: Swets & Zeitlinger
    [Google Scholar]
27. 27.  Hedrick JK, Tomizuka M, Varaiya P 1994. Control issues in automated highway systems. IEEE Control Syst. Mag. 14:621–32
    [Google Scholar]
28. 28.  Swaroop D, Hedrick JK 1996. String stability of interconnected systems. IEEE Trans. Autom. Control 41:4349–56
    [Google Scholar]
29. 29.  Swaroop D, Hedrick JK 1999. Constant spacing strategies for platooning in automated highway systems. J. Dyn. Syst. Meas. Control. 121:462–70
    [Google Scholar]
30. 30.  Shamma JS 2001. A connection between structured uncertainty and decentralized control of spatially invariant systems. Proceedings of the 2001 American Control Conference, June 25–27, Crystal Gateway Marriot, Arlington, VA 43117–21 Piscataway, NJ: IEEE
    [Google Scholar]
31. 31.  Mueller MW, D'Andrea R 2014. Stability and control of a quadrocopter despite the complete loss of one, two, or three propellers. 2014 IEEE International Conference on Robotics and Automation (ICRA), May 31–June 745–52 Piscataway, NJ: IEEE
    [Google Scholar]
32. 32.  Mueller MW, D'Andrea R 2015. Relaxed hover solutions for multicopters: application to algorithmic redundancy and novel vehicles. Int. J. Robot. Res. 35:8873–89
    [Google Scholar]
33. 33.  Mueller MW, Hehn M, D'Andrea R 2015. A computationally efficient motion primitive for quadrocopter trajectory generation. IEEE Trans. Robot. 31:81294–310
    [Google Scholar]
34. 34.  Hehn M, Ritz R, D'Andrea R 2012. Performance benchmarking of quadrotor systems using time-optimal control. Auton. Robots 33:1–269–88
    [Google Scholar]
35. 35.  Houska B, Ferreau H, Diehl M 2011. ACADO toolkit: an open source framework for automatic control and dynamic optimization. Optimal Control Appl. Methods 32:3298–312
    [Google Scholar]
36. 36.  Heater B 2017. MIT's gas-powered drone is able to stay in the air for five days at a time. TechCrunch June 27. https://techcrunch.com/2017/06/27/mits-gas-powered-drone-is-able-to-stay-in-the-air-for-five-days-at-a-time/
37. 37.  Alam M-R, Saadat M, Grenfell PW, Messner S, Jalali M-A 2016. Supermaneuverable autonomous swimmer Paper presented at the 31st Symposium on Naval Hydrodynamics Monterey, CA: Sept 11–16
38. 38.  Mark DB, Hansen SM, Starks ML, Cummings ML 2017. Drone-based automatic external defibrillators for sudden death. Circulation 135:2466–69
    [Google Scholar]
39. 39.  Holland JH 1975. Adaptation in Natural and Artificial Systems Ann Arbor, MI: Univ. Mich. Press
40. 40.  Goldberg DE 1989. Genetic Algorithms in Search, Optimization, and Machine Learning Reading, MA: Addison-Wesley
41. 41.  Davis L 1991. Handbook of Genetic Algorithms New York: Van Nostrand Reinhold
42. 42.  Onwubiko C 2000. Introduction to Engineering Design Optimization Upper Saddle River, NJ: Prentice-Hall
43. 43.  Goldberg DE, Deb K 2000. Special issue on genetic algorithms. Comput. Methods Appl. Mech. Eng. 186:2–4121–24
    [Google Scholar]
44. 44.  Luenberger D 1974. Introduction to Linear and Nonlinear Programming Menlo Park, CA: Addison-Wesley
45. 45.  Gill P, Murray W, Wright M 1982. Practical Optimization Bingley, UK: Emerald Group