Optimal UAV Path Planning: Sensing Data Acquisition Over IoT Sensor Networks Using Multi-Objective Bio-Inspired Algorithms | Zendy

Qin Yang | Zendy; Sang-Jo Yoo | Zendy

Open Access

Optimal UAV Path Planning: Sensing Data Acquisition Over IoT Sensor Networks Using Multi-Objective Bio-Inspired Algorithms

Author(s) -

Qin Yang,

Sang-Jo Yoo

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2812896

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

The use of unmanned aerial vehicles (UAVs) has been considered to be an efficient platform for monitoring critical infrastructures spanning over geographical areas. UAVs have also demonstrated exceptional feasibility when collecting data due to the wide wireless sensor networks in which they operate. Based on environmental information such as prohibited airspace, geo-locational conditions, flight risk, and sensor deployment statistics, we developed an optimal flight path planning mechanism by using multiobjective bio-inspired algorithms. In this paper, we first acquire data sensing points from the entire sensor field, in which UAV communicates with sensors to obtain sensor data, then we determine the best flight path between neighboring acquisition points. Using the proposed joint genetic algorithm and ant colony optimization from possible UAV flight paths, an optimal one is selected in accordance with sensing, energy, time, and risk utilities. The simulation results show that our method can obtain dynamic environmental adaptivity and high utility in various practical situations.

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