Modeling and Simulation of Perching With a Quadrotor Aerial Robot With Passive Bio-inspired Legs and Feet

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
David J. Dunlop ◽  
Mark A. Minor
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Control Approach ◽  
Planning And Control ◽  
Aerial Vehicles ◽  
Physical Experiments ◽  
Control Research ◽  
Physical Prototype ◽  
And Control ◽  
Future Work ◽  
Quadrotor System

Abstract Perching in unmanned aerial vehicles is appealing for reconnaissance, monitoring, communications, and charging. This paper focuses on modeling, simulation, and control of bioinspired perching in unmanned aerial vehicles on cylindrical objects, which will be used for future planning and control research. A modular approach is taken where the quadrotor, legs, feet, and toes are modeled separately and then integrated to form a complete simulation system. New models of these components consider kinematics and dynamics of each element and their coupling through tendons that provide actuation. The integrated model is assembled to simulate a physical prototype and then validated based upon physical experiments to provide calibration. Simulation results evaluate the validated model performing perching with different gripper-perch alignments. The simulation environment developed in this research provides a foundation to research control approaches for use with the discussed passive perching mechanism. The simulation was validated to capture the dynamics of the real perching mechanism. This platform will be used in future work to develop a control approach that will be implemented in a quadrotor system to land and take-off from a perch in a reliable manner.

scholarly journals Evaluation of Reinforcement and Deep Learning Algorithms in Controlling Unmanned Aerial Vehicles

2021 ◽  
Vol 11 (16) ◽  
pp. 7240
Author(s):  
Yalew Zelalem Jembre ◽  
Yuniarto Wimbo Nugroho ◽  
Muhammad Toaha Raza Khan ◽  
Muhammad Attique ◽  
Rajib Paul ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
Physical Environment ◽  
Learning Algorithms ◽  
Q Learning ◽  
Planning And Control ◽  
Aerial Vehicles ◽  
Reinforcement Learning Models ◽  
And Control

Unmanned Aerial Vehicles (UAVs) are abundantly becoming a part of society, which is a trend that is expected to grow even further. The quadrotor is one of the drone technologies that is applicable in many sectors and in both military and civilian activities, with some applications requiring autonomous flight. However, stability, path planning, and control remain significant challenges in autonomous quadrotor flights. Traditional control algorithms, such as proportional-integral-derivative (PID), have deficiencies, especially in tuning. Recently, machine learning has received great attention in flying UAVs to desired positions autonomously. In this work, we configure the quadrotor to fly autonomously by using agents (the machine learning schemes being used to fly the quadrotor autonomously) to learn about the virtual physical environment. The quadrotor will fly from an initial to a desired position. When the agent brings the quadrotor closer to the desired position, it is rewarded; otherwise, it is punished. Two reinforcement learning models, Q-learning and SARSA, and a deep learning deep Q-network network are used as agents. The simulation is conducted by integrating the robot operating system (ROS) and Gazebo, which allowed for the implementation of the learning algorithms and the physical environment, respectively. The result has shown that the Deep Q-network network with Adadelta optimizer is the best setting to fly the quadrotor from the initial to desired position.

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.

Design And Control Of Plasma Actuated Unmanned Aerial Vehicles (UAV)

2017 ◽  
Author(s):  
Magesh T. Rajan ◽  
Hao Xu ◽  
Clyde Avalos ◽  
Anthony Matheson ◽  
Eric Swinny
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles ◽  
And Control

Systematic Modeling of Rotor-Driving Dynamics for Small Unmanned Aerial Vehicles

2018 ◽  
Vol 06 (02) ◽  
pp. 81-93
Author(s):  
Limin Wu ◽  
Yijie Ke ◽  
Ben M. Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Frequency Domain ◽  
Frequency Domain Analysis ◽  
Speed Controller ◽  
Aerial Vehicles ◽  
Dynamics And Control ◽  
Semi Empirical ◽  
And Control ◽  
Cifer Software ◽  
Systematic Modeling

This paper proposes a systematic modeling approach of rotor-driving dynamics for small unmanned aerial vehicles (UAVs) based on system identification and first principle-based methods. Both steady state response analyses and frequency-domain identifications are conducted for the rotor, and Comprehensive Identification from Frequency Responses (CIFER) software is mainly utilized for the frequency-domain analysis. Moreover, a novel semi-empirical model integrating the rotor and the electrical speed controller is presented and validated. The demonstrated results and model are promising in UAV dynamics and control applications.

Sensorship: the seen unseen of drone warfare

2016 ◽  
Author(s):  
Tom Holert
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Military Operations ◽  
Legal Problems ◽  
Aerial Vehicles ◽  
Drone Warfare ◽  
And Control ◽  
The Military ◽  
Blind Spots

Contemporary warfare has been significantly transformed by the promotion and implementation of unmanned aerial vehicles (or drones) into global military operations. Networked remote sensory vision and the drones’ capability to carry deadly missiles entail and facilitate increasingly individualised, racialised, and necropolitical military practices conceptualised as ‘surgical strikes’ or ‘targeted killings’, all in the name of ‘counterinsurgency’. In the absence of publicly accessible documentations of ‘drone vision’, images of drones themselves constitute what is arguably one of the most contested iconographies of the present. The ethical and legal problems engendered by the virtualisation of violence and the panoptical fantasies of persistent vision and continuous threat interfere with the commercial interests and the publicised ideas of ‘clean’ warfare of the military-industrial-media complex. Drones have become a fetishised icon of warfare running out of human measure and control and are henceforth challenged by activist strategies highlighting the blind spots and victims of their deployment.

scholarly journals A Quadral-Fuzzy Control Approach to Flight Formation by a Fleet of Unmanned Aerial Vehicles

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 64366-64381 ◽  
Author(s):  
Marco Antonio Simoes Teixeira ◽  
Flavio Neves-Jr ◽  
Anis Koubaa ◽  
Lucia Valeria Ramos De Arruda ◽  
Andre Schneider De Oliveira
Keyword(s):  
Fuzzy Control ◽  
Unmanned Aerial Vehicles ◽  
Control Approach ◽  
Aerial Vehicles ◽  
Flight Formation
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