Abstract
This paper proposes a guidance system with a new hybrid architecture for multiple fixed-wing unmanned aerial vehicles (UAVs) formation flight. The proposed architecture is hybrid in the sense of combining two control policies found in guidance systems: the Decentralized Partially Observable Markov Decision Process (Dec-POMDP) policy and the well-known PID controller. The Dec-POMDP policy part enables every UAV to avoid collision with any other UAV from the formation. The PID part is activated for regions far from the collision risk zone and is implemented in such a way that each UAV is completely controlled by only its own data, independent of its neighbors. The major novelty of the proposed system, compared to other hybrid approaches, is its decentralized nature which favors overcoming the usual problems that come with centralization such as the high dependence on a central decision node, a leader, or a ground station. Inherited from both parts, the overall system performance is robust in noisy and uncertain environments. Simulations were extensively performed to show the effectiveness of the proposed guidance system in distinct scenarios.
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Acknowledgements
The authors would like to thank the Brazilian National Council for the Improvement of Higher Education (CAPES) and the Brazilian National Council of Scientific and Technological Development (CNPq) for the support.
Funding
This research was funded to the researchers Bruno R. O. Floriano and João Y. Ishihara, respectively, by the institutions:
– Brazilian National Council for the Improvement of Higher Education (CAPES)
– Brazilian National Council of Scientific and Technological Development (CNPq)
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All authors contributed to the study conception, design and methodology. Bruno R. O. Floriano was also responsible for the investigation, software and writing. Geovany A. Borges, Henrique C. Ferreira and João Y. Ishihara were also responsible for writing and revision. All authors read and approved the final manuscript.
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Appendix: A
Appendix: A
1.1 A.1 Transition Matrices
The transition probability matrices used in Section 5, \({T^{i}_{v}}\) and \(T^{i}_{\omega }\), are described as follows (the number in parentheses is the index βv and βω that multiplies the base values αvb or αωb respectively, of each matrix):
in which I is the 8-th dimensional identity matrix and 18x8 is the 8-th dimensional square matrix completely filled with 1.
Due to the symmetry of the problem:
1.2 A.2 Proof of Eq. 5
There is a total of N agents that get some observation zi. However, a total of \(N_{\zeta _{i}} = j\) of those agents that perceive \(z_{i} = s^{\prime }\) can be allocated. Since these agents were fixed, there are another N − j agents that might observe any from the \(N_{z_{i}} - 1\) observations in which \(z_{i} \neq s^{\prime }\). In this arrangement, the number of combinations is given by
However, there are other arrangements for the j agents that observe \(z_{i} = s^{\prime }\). The number of possible permutations to fix those agents is given by
For each arrangement, there are Ncomb combinations so the total number of combinations, Dj, is given by
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Floriano, B.R.O., Borges, G.A., Ferreira, H.C. et al. Hybrid Dec-POMDP/PID Guidance System for Formation Flight of Multiple UAVs. J Intell Robot Syst 101, 65 (2021). https://doi.org/10.1007/s10846-021-01342-0
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DOI: https://doi.org/10.1007/s10846-021-01342-0