scholarly journals Cooperative Multi-UAV Conflict Avoidance Planning in a Complex Urban Environment

2021 ◽  
Vol 13 (12) ◽  
pp. 6807
Author(s):  
Kaiping Wang ◽  
Mingzhu Song ◽  
Meng Li
Keyword(s):  
Urban Environment ◽  
Trajectory Planning ◽  
System Level ◽  
Conflict Avoidance ◽  
Multiple Traveling Salesman Problem ◽  
Time Graph ◽  
Proposed Model ◽  
Aerial Vehicle ◽  
Upper Level ◽  
Multi Uav

Trajectory planning is of great value and yet challenging for multirotor unmanned aerial vehicle (UAV) applications in a complex urban environment, mainly due to the complexities of handling cluttered obstacles. The problem further complicates itself in the context of autonomous multi-UAV trajectory planning considering conflict avoidance for future city applications. To tackle this problem, this paper introduces the multi-UAV cooperative trajectory planning (MCTP) problem, and proposes a bilevel model for the problem. The upper level is modeled as an extended multiple traveling salesman problem, aiming at generating trajectories based on heuristic framework for multi-UAV task allocation and scheduling and meanwhile considering UAV kinodynamic properties. The lower level is modeled as a holding time assignment problem to avoid possible spatiotemporal trajectory conflicts, where conflict time difference is analyzed based on the proposed state-time graph method. Numerical studies are conducted in both a 1 km2 virtual city and 12 km2 real city with a set of tasks and obstacles settings. The results show that the proposed model is capable of planning trajectories for multi-UAV from the system-level perspective based on the proposed method.

Cuckoo search-based method for trajectory planning of quadrotor in an urban environment

2019 ◽  
Vol 233 (12) ◽  
pp. 4571-4582 ◽  
Author(s):  
Hanjie Hu ◽  
Yu Wu ◽  
Jinfa Xu ◽  
Qingyun Sun
Keyword(s):  
Urban Environment ◽  
Trajectory Planning ◽  
Cuckoo Search ◽  
General Idea ◽  
Planning Problem ◽  
Safety Level ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Express Industry ◽  
Easy Operation

Express by micro aerial vehicle (MAV) becomes more and more popular because it can avoid the influence of terrain and save more space for taking-off and landing of aircraft. At present, quadrotor is often used in the express industry due to its flexibility and easy operation, and the flight trajectory plays an important role in the efficiency and safety level of express service. In this paper, the trajectory planning problem is studied for quadrotor delivering goods in urban environment with the purpose of avoiding the heavy ground traffic, and a cuckoo search (CS)-based trajectory planning method is proposed to solve the problem. First, a conceptual model containing all the key elements of the delivery task is developed, which presents a general idea of solving the problem. Some characteristics of the urban environment and the delivery task, such as the wind field, dense buildings and inclination of shipped goods, are taken into account in the trajectory planning model. The goal of the delivery task is to make the goods reach the destination accurately. When designing the CS-based trajectory planning algorithm, the basics of CS algorithm are explained, and then it is integrated into the trajectory planning problem. Comparative experiments are carried out to investigate the superiority of the proposed method, and the influences of parameters in CS algorithm are also discussed to conclude its performance in trajectory planning problem.

Fast Transaction-Level Model for Direct Memory Access Controller

2019 ◽  
Vol 28 (04) ◽  
pp. 1950059
Author(s):  
Mona Safar ◽  
Magdy A. El-Moursy ◽  
Ahmed Tarek ◽  
Ahmed Emad ◽  
Ahmed Hesham ◽  
...  
Keyword(s):  
Open Source ◽  
Direct Memory Access ◽  
System Level ◽  
The Past ◽  
Simulation Speed ◽  
Proposed Model ◽  
Level Model ◽  
Data Bus ◽  
Transaction Level ◽  
Simulation Time

Transaction-Level Modeling (TLM) has been widely used in system-level design in the past few years. Simulation speed of Virtual Platforms (VPs) depends mainly on the transactions which are initiated by the Programmer’s View (PV) models of the VP devices. PV models are required to run at highest simulation speed. Data bus width as a hardware (HW) parameter should not reduce simulation speed of the modeled transactions. Furthermore, HW-related parameters should only be accounted for when considering timing of the models. A fast SystemC-TLM model is developed for the widely used ARM PrimeCell PL080 DMAC IP. The performance of the proposed model is validated against a developed RTL model for the same device. The effect of the transactions granularity on simulation speed is determined. Different programmed transfers are simulated and compared with open-source Quick Emulator (QEMU)-based models. The developed model is compared with the developed RTL, the open-source QEMU model, and the existing ARM Fast Model (AFM). It is shown that simulation time of the developed model is reduced by two orders of magnitude as compared to the other existing models.

Multi-UAV Cooperative Task Planning for Border Patrol based on Hierarchical Optimization

2021 ◽  
Author(s):  
Hai-shi Liu ◽  
Yu-xuan Sun ◽  
Nan Pan ◽  
Qi-yong Chen ◽  
Xiao-jue Guo ◽  
...  
Keyword(s):  
Chaos Theory ◽  
Hierarchical Optimization ◽  
Border Patrol ◽  
Complex Environments ◽  
Environmental Model ◽  
Other Information ◽  
Aerial Vehicle ◽  
Scene Information ◽  
Simulation Results ◽  
Multi Uav

In order to improve the patrol efficiency of border patrol drones, based on unmanned aerial vehicle (UAV) border patrol missions in multiple complex environments, this article proposes a whale algorithm based on chaos theory to plan patrol missions for multiple drones. First, according to the terrain the corresponding environmental model is established for the topography and then solved in layers to obtain the number of drones and other information that each base needs to send to the patrol area. Further, the use of drones with cameras and other detection equipment to patrol the scene information and images extract and transfer to the terminal in real time, and further detect suspicious persons and vehicles on the screen. The final simulation results show that the proposed scheme can be effectively applied to the planning of multi-UAV coordinated missions for border patrol.

Optimal Control of a Multirotor Unmanned Aerial Vehicle Based on a Multiphysical Model

2020 ◽  
Author(s):  
Nicolas Michel ◽  
Zhaodan Kong ◽  
Xinfan Lin
Keyword(s):  
Optimal Control ◽  
Unmanned Aerial Vehicle ◽  
Operation Time ◽  
Rigid Body Dynamics ◽  
System Level ◽  
Optimal Velocity ◽  
Rotor Aerodynamics ◽  
Time Optimal ◽  
Aerial Vehicle ◽  
Level Model

Abstract Electric multirotor aircraft with vertical-take-off-and-landing capabilities are emerging as a revolutionary transportation mode. This paper studies optimal control of a multirotor unmanned aerial vehicle based on a system-level multiphysical model. The model considers aerodynamics of the rotor-propeller assembly, electro-mechanical dynamics of the motor and motor controller, and rigid-body dynamics of the vehicle, as control based on a system-level model incorporating all these dynamics and their coupling is missing in literature. A forward flight operation is considered for time-optimal and energy-optimal control, as well as battery voltages of 25 V and 21 V. Energy-optimal control is shown to reduce the energy required for the operation by 38.5% at 25 V, while reducing the battery voltage increases the minimum operation time by 19.8%. The energy-optimal cruise velocity is also examined, demonstrating that the optimal velocity predicted without considering rotor aerodynamics uses 35.2% more energy per meter travelled than is required at the true optimal velocity.

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

2019 ◽  
Vol 233 (16) ◽  
pp. 6032-6043 ◽  
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Potential Field ◽  
Three Dimensional ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Vehicle Trajectory

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

scholarly journals Information Distribution in Multi-Robot Systems: Utility-Based Evaluation Model

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 710 ◽  
Author(s):  
Michał Barciś ◽  
Agata Barciś ◽  
Hermann Hellwagner
Keyword(s):  
Evaluation Model ◽  
Proof Of Concept ◽  
Information Distribution ◽  
Unified Framework ◽  
Robot Operating System ◽  
Robot Systems ◽  
System 2 ◽  
Aerial Vehicle ◽  
Multi Uav ◽  
Multi Robot

This work addresses the problem of information distribution in multi-robot systems, with an emphasis on multi-UAV (unmanned aerial vehicle) applications. We present an analytical model that helps evaluate and compare different information distribution schemes in a robotic mission. It serves as a unified framework to represent the usefulness (utility) of each message exchanged by the robots. It can be used either on its own in order to assess the information distribution efficacy or as a building block of solutions aimed at optimizing information distribution. Moreover, we present multiple examples of instantiating the model for specific missions. They illustrate various approaches to defining the utility of different information types. Finally, we introduce a proof of concept showing the applicability of the model in a robotic system by implementing it in Robot Operating System 2 (ROS 2) and performing a simple simulated mission using a network emulator. We believe the introduced model can serve as a basis for further research on generic solutions for assessing or optimizing information distribution.

Multi-UAV Specification and Control with a Single Pilot-in-the-Loop

2020 ◽  
Vol 08 (04) ◽  
pp. 269-277
Author(s):  
Patricio Moreno ◽  
Santiago Esteva ◽  
Ignacio Mas ◽  
Juan I. Giribet
Keyword(s):  
Remote Control ◽  
Unmanned Aerial Vehicles ◽  
Field Experiments ◽  
Aerial Vehicles ◽  
Simulated Environment ◽  
Aerial Vehicle ◽  
Space Formulation ◽  
Trajectory Following ◽  
And Control ◽  
Multi Uav

This work presents a multi-unmanned aerial vehicle formation implementing a trajectory-following controller based on the cluster-space robot coordination method. The controller is augmented with a feed-forward input from a control station operator. This teleoperation input is generated by means of a remote control, as a simple way of modifying the trajectory or taking over control of the formation during flight. The cluster-space formulation presents a simple specification of the system’s motion and, in this work, the operator benefits from this capability to easily evade obstacles by means of controlling the cluster parameters in real time. The proposed augmented controller is tested in a simulated environment first, and then deployed for outdoor field experiments. Results are shown in different scenarios using a cluster of three autonomous unmanned aerial vehicles.

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