Cooperative pursue in pursuit-evasion games with unmanned aerial vehicles
This work tackles the problem of pursuit-evasion games between two pursuing and one evading unmanned aerial vehicle. The solution of this problem is derived by introducing a hierarchical decomposition of the game. On a superordinate collaboration level, the pursuers choose their optimal behavioral s...
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| Main Authors: | , , |
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| Format: | Article (Journal) Chapter/Article |
| Language: | English |
| Published: |
17 December 2015
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| In: |
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2015, Pages: 4538-4543 |
| DOI: | 10.1109/IROS.2015.7354022 |
| Online Access: | Verlag, Volltext: https://ieeexplore.ieee.org/document/7354022 Resolving-System, Volltext: http://dx.doi.org/10.1109/IROS.2015.7354022 
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| Author Notes: | Alexander Alexopoulos, Tobias Schmidt and Essameddin Badreddin |
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| 520 | |a This work tackles the problem of pursuit-evasion games between two pursuing and one evading unmanned aerial vehicle. The solution of this problem is derived by introducing a hierarchical decomposition of the game. On a superordinate collaboration level, the pursuers choose their optimal behavioral strategy (i.e. pursue and herd) resulting in a three-player non-cooperative dynamic game which is solved in a subordinate level of the overall game. This structure enables an intelligent behavior change for the pursuers based on game-theoretical solution methods. Depending on the state of the game it has to be evaluated which behavioral strategy yields the best results for the pursuers within the regarded time horizon. It is shown, that the pursuer's outcome can be improved by using a superordinate cooperation between them. Furthermore, this application was implemented on a real quad-rotor system. In experiments the quad-rotor teamed-up with a software-emulated pursuer and it was shown that another software-emulated quad-rotor was caught. This framework provides a solution concept for all types of dynamic games with an arbitrary number of players and teams having a non-cooperative and cooperative nature. The hierarchical decomposition gives more flexibility and allows team members to co-ordinate their behavior and thus to maximize their outcome. | ||
| 650 | 4 | |a Attitude control | |
| 650 | 4 | |a autonomous aerial vehicles | |
| 650 | 4 | |a Computers | |
| 650 | 4 | |a cooperative pursue | |
| 650 | 4 | |a game theory | |
| 650 | 4 | |a game-theoretical solution methods | |
| 650 | 4 | |a Games | |
| 650 | 4 | |a hierarchical decomposition | |
| 650 | 4 | |a intelligent behavior change | |
| 650 | 4 | |a Mathematical model | |
| 650 | 4 | |a noncooperative dynamic game | |
| 650 | 4 | |a optimal behavioral strategy | |
| 650 | 4 | |a pursuit-evasion games | |
| 650 | 4 | |a Robot sensing systems | |
| 650 | 4 | |a Rotors | |
| 650 | 4 | |a superordinate collaboration level | |
| 650 | 4 | |a unmanned aerial vehicles | |
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| 700 | 1 | |a Badreddin, Essameddin |e VerfasserIn |0 (DE-588)1136732853 |0 (DE-627)893510246 |0 (DE-576)490797644 |4 aut | |
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