By Tal Shima, Steven Rasmussen
Unmanned aerial automobiles (UAVs) are more and more utilized in army missions simply because they've got the benefits of no longer putting human lifestyles in danger and of reducing operation charges through diminished automobile weight. those advantages should be absolutely discovered provided that UAVs paintings cooperatively in teams with a good alternate of knowledge. This e-book offers an authoritative reference on cooperative choice and keep watch over of UAVs and the skill on hand to resolve difficulties regarding them.
The participants current the knowledge in a fashion that abstracts the demanding situations from the concrete difficulties, making it attainable to leverage the answer equipment over a broader variety of purposes. the 1st bankruptcy bargains consultant situations to explain the matter and its demanding situations. the second one bankruptcy heavily examines those demanding situations via delivering an summary of the algorithms which may be used for cooperative keep watch over of UAV groups. Later chapters supply tools for appearing a number of projects on a number of ambitions and assigning a number of projects to a number of UAVs in a single step. different issues addressed are the appliance of combined integer linear programming and genetic algorithms in events with strict time constraints, the cooperation of UAVs while there are verbal exchange delays, and effectiveness measures derived for operations in doubtful environments.
The booklet has appendices. the 1st describes the operation of the MultiUAV2 simulation software program used to check the cooperation keep an eye on algorithms, whereas the second one information the UAV course making plans challenge and Dubins optimum trajectories. A supplementary web site bargains a MultiUAV2 software program handbook and proper code.
Audience: The e-book is essentially aimed toward researchers engaged on functional ideas for enforcing structures with a number of UAVs. Academicians, scholars, and others who are looking to comprehend the sector of UAV cooperative regulate will locate this e-book an invaluable reference.
Contents: record of Figures; checklist of Tables; Foreword; Preface; Acronyms; bankruptcy 1: advent; bankruptcy 2: demanding situations; bankruptcy three: unmarried job excursions; bankruptcy four: a number of Assignments; bankruptcy five: Simultaneous a number of Assignments; bankruptcy 6: Estimation Algorithms for greater Cooperation less than Uncertainty; bankruptcy 7: Effectiveness Measures for Operations in doubtful Environments; Appendix A: MutliUAV Simulation; Appendix B: course making plans for UAVs; Index
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Additional resources for UAV cooperative decision and control: challenges and practical approaches
Concepts for generating coherent radar phantom tracks using cooperating vehicles. In Proceedings of the AIAA Guidance, Navigation, and Control Conference, Providence, RI, 2004.  C. M. Peebles. S. Aircraft Programs. Presidio Press, Novato, CA, 1999.  A. C. Piccirillo. The origins of the anti-ship guided missile. In Proceedings of the 1997 World Aviation Congress Conference, Anaheim, CA, 1997.  T. Shima and C. Schumacher. Assigning cooperating UAVs to simultaneous tasks on consecutive targets using genetic algorithms.
In a team, by construction, the objectives are basically compatible. We now address the control of UAVs that are operating in teams that are competing and, possibly, adversarial. If there are two teams, this is the domain of a significant part of game theory research. , bimatrix games [33, 63]. This is the field of much military research, as in the war game of Blue team versus Red team. However, the field is much richer than this, because in reality there can also be, for example, a White team and a Green team.
The challenge is to calculate the expected future value of a decision or action taken now. For example, if the UAVs use their resources on targets now, there may be no reserves left for targets that are found later and that have higher value [20, 22, 54]. At the same time, actions taken now might decrease the level of uncertainty. The latter can be gauged using information theoretic concepts. Possible choices are to myopically follow the decision path of least risk or to follow the decision path that maximizes the possible options in the future.