scholarly journals Design and Analysis of Collaborative Unmanned Surface-Aerial Vehicle Cruise Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Man Zhu ◽  
Yuan-Qiao Wen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Command And Control ◽  
Collaborative Model ◽  
Weighting Method ◽  
Unmanned Surface Vehicle ◽  
Control Networks ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
And Control

With the increasing application of unmanned surface vehicle-unmanned aerial vehicles (USV-UAVs) in maritime supervision, research on their deployment and control is becoming vitally important. We investigate the application of USV-UAVs for synergistic cruising and evaluate the effectiveness of the proposed collaborative model. First, we build a collaborative model consisting of the cruise vehicles and communication, detection, and command-and-control networks for the USV-UAV. Second, based on an analysis of the problems faced by collaborative USV-UAV systems, we establish a model to evaluate the effectiveness of such synergistic cruises. Third, we propose a weighting method for each evaluation factor. Finally, a model consisting of one UAV and four USVs is employed to validate our synergistic cruise model.

Modeling and control of a quadrotor tail-sitter unmanned aerial vehicles

2021 ◽  
pp. 095965182110504
Author(s):  
Hongbo Xin ◽  
Yujie Wang ◽  
Xianzhong Gao ◽  
Qingyang Chen ◽  
Bingjie Zhu ◽  
...  
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Euler Angle ◽  
Level Flight ◽  
Aerial Vehicles ◽  
Flight Mode ◽  
Aerial Vehicle ◽  
Hover Flight ◽  
And Control

The tail-sitter unmanned aerial vehicles have the advantages of multi-rotors and fixed-wing aircrafts, such as vertical takeoff and landing, long endurance and high-speed cruise. These make the tail-sitter unmanned aerial vehicle capable for special tasks in complex environments. In this article, we present the modeling and the control system design for a quadrotor tail-sitter unmanned aerial vehicle whose main structure consists of a traditional quadrotor with four wings fixed on the four rotor arms. The key point of the control system is the transition process between hover flight mode and level flight mode. However, the normal Euler angle representation cannot tackle both of the hover and level flight modes because of the singularity when pitch angle tends to [Formula: see text]. The dual-Euler method using two Euler-angle representations in two body-fixed coordinate frames is presented to couple with this problem, which gives continuous attitude representation throughout the whole flight envelope. The control system is divided into hover and level controllers to adapt to the two different flight modes. The nonlinear dynamic inverse method is employed to realize fuselage rotation and attitude stabilization. In guidance control, the vector field method is used in level flight guidance logic, and the quadrotor guidance method is used in hover flight mode. The framework of the whole system is established by MATLAB and Simulink, and the effectiveness of the guidance and control algorithms are verified by simulation. Finally, the flight test of the prototype shows the feasibility of the whole system.

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.

Using Heart Rate Variability to Assess Operator Mental Workload in a Command and Control Simulation of Multiple Unmanned Aerial Vehicles

2016 ◽  
Vol 60 (1) ◽  
pp. 1125-1129 ◽  
Author(s):  
Phillip Jasper ◽  
Ciara Sibley ◽  
Joseph Coyne
Keyword(s):  
Heart Rate ◽  
Unmanned Aerial Vehicles ◽  
Mental Workload ◽  
Command And Control ◽  
Control Simulation ◽  
Aerial Vehicles ◽  
Single Vehicle ◽  
Multiple Unmanned Aerial Vehicles ◽  
And Control ◽  
Operator Workload

Unmanned systems will play an increased role in the future beyond military application including but not limited to: search and rescue, border patrol, homeland security, and natural disaster relief operations. Current models of unmanned system operations, such as those used for unmanned aerial vehicles, require multiple operators to control a single vehicle. This multioperator-single vehicle ratio will soon shift to a multioperator-multivehicle model as the number of unmanned systems increase and work in unison to complete a mission. The purpose of this study was to determine the utility of a physiological measure i.e. heart rate variability (HRV), to assess operator workload in a single operator-multivehicle command and control simulation. An internally developed command and control simulator is described and observed effects of mental workload on HRV are reported. Results suggest that HRV can be used to assess operator workload during a command and control simulation of multiple unmanned aerial vehicles.

The Human Challenges of Command and Control with Multiple Unmanned Aerial Vehicles

2005 ◽  
Vol 49 (1) ◽  
pp. 20-24 ◽  
Author(s):  
Bruce P. Hunn
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles ◽  
Vehicle Operation ◽  
Aerial Vehicle ◽  
Remote Sites ◽  
Unmanned System ◽  
Multiple Unmanned Aerial Vehicles ◽  
And Control ◽  
Direct Feedback ◽  
Display Systems

The unmanned aerial vehicle represents a significant challenge to its operators since they are literally out of touch with the system they control. Operating from remote sites miles from the vehicle they control, they are isolated by space and time from a direct connection to the machine they operate. While the pilot of a manned aircraft can always receive some type of direct feedback from the machine they operate, even if they lose all their control and display systems, they can still perceive many qualities of that machine's system state merely from their senses. However, in contrast, the unmanned system is based solely on an electronic link connecting the operator to their vehicle. This paper will review the historical trends in remote vehicle operation and discuss state-of-the-art in remote control systems as they apply to single or multiple unmanned aerial vehicles.

scholarly journals Autonomous Vision-Based Aerial Grasping for Rotorcraft Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3410 ◽  
Author(s):  
Lishan Lin ◽  
Yuji Yang ◽  
Hui Cheng ◽  
Xuechen Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Region Of Interest ◽  
Target Object ◽  
Robotic Arm ◽  
Support Vector ◽  
Control Laws ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
And Control ◽  
High Computational Efficiency

Autonomous vision-based aerial grasping is an essential and challenging task for aerial manipulation missions. In this paper, we propose a vision-based aerial grasping system for a Rotorcraft Unmanned Aerial Vehicle (UAV) to grasp a target object. The UAV system is equipped with a monocular camera, a 3-DOF robotic arm with a gripper and a Jetson TK1 computer. Efficient and reliable visual detectors and control laws are crucial for autonomous aerial grasping using limited onboard sensing and computational capabilities. To detect and track the target object in real time, an efficient proposal algorithm is presented to reliably estimate the region of interest (ROI), then a correlation filter-based classifier is developed to track the detected object. Moreover, a support vector regression (SVR)-based grasping position detector is proposed to improve the grasp success rate with high computational efficiency. Using the estimated grasping position and the UAV?Äôs states, novel control laws of the UAV and the robotic arm are proposed to perform aerial grasping. Extensive simulations and outdoor flight experiments have been implemented. The experimental results illustrate that the proposed vision-based aerial grasping system can autonomously and reliably grasp the target object while working entirely onboard.

scholarly journals Obstacle avoidance and distance measurement for unmanned aerial vehicles using monocular vision

2019 ◽  
Vol 9 (5) ◽  
pp. 3504
Author(s):  
Aswini N ◽  
Uma S V
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Obstacle Avoidance ◽  
Communication Systems ◽  
Scale Invariant ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Complex Automation ◽  
Novel Method ◽  
Scale Invariant Feature ◽  
And Control

<span lang="EN-US">Unmanned Aerial Vehicles or commonly known as drones are better suited for "dull, dirty, or dangerous" missions than manned aircraft. The drone can be either remotely controlled or it can travel as per predefined path using complex automation algorithm built during its development. In general, Unmanned Aerial Vehicle (UAV) is the combination of Drone in the air and control system on the ground. Design of an UAV means integrating hardware, software, sensors, actuators, communication systems and payloads into a single unit for the application involved. To make it completely autonomous, the most challenging problem faced by UAVs is obstacle avoidance. In this paper, a novel method to detect frontal obstacles using monocular camera is proposed. Computer Vision algorithms like Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Feature (SURF) are used to detect frontal obstacles and then distance of the obstacle from camera is calculated. To meet the defined objectives, designed system is tested with self-developed videos which are captured by DJI Phantom 4 pro.</span>

A constraint-based approach for planning unmanned aerial vehicle activities

2016 ◽  
Vol 31 (5) ◽  
pp. 486-497
Author(s):  
Christophe Guettier ◽  
François Lucas
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicles ◽  
User Acceptance ◽  
Mission Planning ◽  
Planning Problem ◽  
Aerial Vehicles ◽  
Mission Duration ◽  
Aerial Vehicle ◽  
Global Planning ◽  
And Control

AbstractUnmanned Aerial Vehicles (UAV) represent a major advantage in defense, disaster relief and first responder applications. UAV may provide valuable information on the environment if their Command and Control (C2) is shared by different operators. In a C2 networking system, any operator may request and use the UAV to perform a remote sensing operation. These requests have to be scheduled in time and a consistent navigation plan must be defined for the UAV. Moreover, maximizing UAV utilization is a key challenge for user acceptance and operational efficiency. The global planning problem is constrained by the environment, targets to observe, user availability, mission duration and on-board resources. This problem follows previous research works on automatic mission Planning & Scheduling for defense applications. The paper presents a full constraint-based approach to simultaneously satisfy observation requests, and resolve navigation plans.

Sign in / Sign up

Export Citation Format

Share Document