Fuzzy logic, neural-fuzzy network and honey bees algorithm to develop the swarm motion of aerial robots

Autor: Jamshid Sardari, Mohammad Siami Araghi, Shervin Zahedi, Iman Shafieenejad, Elham Dehghan Rouzi, Amirhosein Esmaeili
Rok vydání: 2021
Předmět:
Zdroj: Evolving Systems. 13:319-330
ISSN: 1868-6486
1868-6478
DOI: 10.1007/s12530-021-09391-4
Popis: In this study, a novel nature-inspired autonomous motion was investigated using the honey-bee algorithm for aerial robots. The main idea belonged to a novel analogy between optimal honey bees and aerial robots’ motion in proposing autonomous guidance. Three-dimensional simulations for aerial robots were considered to show the efficient performance of autonomous guidance. A new equation system was also developed based on the yaw angle control to simplify dynamic flight calculations. Moreover, different uncertainties such as lateral wind current and navigation’ noise were considered and checked precisely using a neural-fuzzy network to enhance autonomous guidance reliability. Accordingly, aerial robots’ autonomous motions were developed by fuzzy logic to overcome low-quality data linkages between aerial robots. The results of this study illustrated that the integrated nature-inspired guidance by fuzzy logic had a lower total passing and the final time of 24.64% and 21.87% for aerial robots, respectively.
Databáze: OpenAIRE
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