Next Article in Journal
Early Output Quasi-Delay-Insensitive Array Multipliers
Next Article in Special Issue
Active Disturbance Rejection Control of Multi-Joint Industrial Robots Based on Dynamic Feedforward
Previous Article in Journal
A Novel Approach towards Resource Auto-Registration and Discovery of Embedded Systems Based on DNS
Previous Article in Special Issue
Advanced Backstepping Trajectory Control for Skid-Steered Duct-Cleaning Mobile Platforms
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle

A Hierarchical Cooperative Mission Planning Mechanism for Multiple Unmanned Aerial Vehicles

1
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
2
PLA 66133 Troops, Beijing 100144, China
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(4), 443; https://doi.org/10.3390/electronics8040443
Received: 15 March 2019 / Revised: 7 April 2019 / Accepted: 12 April 2019 / Published: 18 April 2019
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
  |  
PDF [3503 KB, uploaded 18 April 2019]
  |  

Abstract

In this paper, the cooperative multi-task online mission planning for multiple Unmanned Aerial Vehicles (UAVs) is studied. Firstly, the dynamics of unmanned aerial vehicles and the mission planning problem are studied. Secondly, a hierarchical mechanism is proposed to deal with the complex multi-UAV multi-task mission planning problem. In the first stage, the flight paths of UAVs are generated by the Dubins curve and B-spline mixed method, which are defined as “CBC)” curves, where “C” stands for circular arc and “B” stands for B-spline segment. In the second stage, the task assignment problem is solved as multi-base multi-traveling salesman problem, in which the “CBC” flight paths are used to estimate the trajectory costs. In the third stage, the flight trajectories of UAVs are generated by using Gaussian pseudospectral method (GPM). Thirdly, to improve the computational efficiency, the continuous and differential initial trajectories are generated based on the “CBC” flight paths. Finally, numerical simulations are presented to demonstrate the proposed approach, the designed initial solution search algorithm is compared with existing methods. These results indicate that the proposed hierarchical mission planning method can produce satisfactory mission planning results efficiently. View Full-Text
Keywords: Multi-UAV cooperative mission planning; B-spline; dubins curves; guassian pseudospectral method Multi-UAV cooperative mission planning; B-spline; dubins curves; guassian pseudospectral method
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Zhao, Z.; Yang, J.; Niu, Y.; Zhang, Y.; Shen, L. A Hierarchical Cooperative Mission Planning Mechanism for Multiple Unmanned Aerial Vehicles. Electronics 2019, 8, 443.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Electronics EISSN 2079-9292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top