Using Optimization, Learning, and Drone Reflexes to Maximize Safety of Swarms of Drones

Amin Majd, Adnan Ashraf, Elena Troubitsyna, Masoud Daneshtalab

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

6 Sitaatiot (Scopus)

Abstrakti

Despite the growing popularity of swarm-based applications of drones, there is still a lack of approaches to maximize the safety of swarms of drones by minimizing the risks of drone collisions. In this paper, we present an approach that uses optimization, learning, and automatic immediate responses (reflexes) of drones to ensure safe operations of swarms of drones. The proposed approach integrates a high-performance dynamic evolutionary algorithm and a reinforcement learning algorithm to generate safe and efficient drone routes and then augments the generated routes with dynamically computed drone reflexes to prevent collisions with unforeseen obstacles in the flying zone. We also present a parallel implementation of the proposed approach and evaluate it against two benchmarks. The results show that the proposed approach maximizes safety and generates highly efficient drone routes.

AlkuperäiskieliEi tiedossa
Otsikko2018 IEEE Congress on Evolutionary Computation (CEC)
ToimittajatCarlos Coello Coello, Hisao Ishibuchi, Li Xiaodong, Fernando Von Zuben
KustantajaIEEE
Sivut1–8
ISBN (elektroninen)978-1-5090-6017-7
ISBN (painettu)978-1-5090-6018-4
DOI - pysyväislinkit
TilaJulkaistu - 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaIEEE Congress on Evolutionary Computation (CEC) - IEEE Congress on Evolutionary Computation (CEC)
Kesto: 8 heinäkuuta 201813 heinäkuuta 2018

Konferenssi

KonferenssiIEEE Congress on Evolutionary Computation (CEC)
Ajanjakso08/07/1813/07/18

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