A review of aerial manipulation of small-scale rotorcraft unmanned robotic systems

Ding, Xilun; Pin, Guo; Xu, Kun; Yu, Yushu

doi:10.1016/j.cja.2018.05.012

Cited by 104 publications

(35 citation statements)

References 48 publications

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“…For example, in military, it can replace human-machines to accomplish certain tasks in harsh environments and high risks [1]. In civil applications, it has been widely used in agriculture, services and other areas such as spraying pesticides, geological exploration, archaeological exploration, logistics and transportation [2], [3]. Regardless of military career or civilian market, the breakthrough in technical of UAV means a significant increase in work efficiency [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

UAVs’ Formation Keeping Control Based on Multi–Agent System Consensus

2020

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In this paper, formation keeping control of unmanned aerial vehicles (UAVs) based on multi-agent system consensus is studied. Firstly, a leader-following model based multiple unmanned aerial vehicles' (multi-UAVs') formation system is proposed. In which, every UAV has a heading keep autopilot as standard flight controller, and the heading control signal is transmitted by a nonlinear feedback controller with time delays. Secondly, some criteria of stability and Hopf bifurcation conditions for the equilibrium point of the leader UAV are established by using the Routh-Hurwitz criterion. Then, the consensus protocol is designed. A model prediction controller is introduced to make followers predict the leader's status and maintain a relative position in the formation, and eventually reach a consensus with the leader. Finally, some simulation examples are given to verify the correctness of the conclusions.

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Section: Introductionmentioning

confidence: 99%

UAVs’ Formation Keeping Control Based on Multi–Agent System Consensus

2020

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“…Due to its flying ability, it can easily cover large distance quickly with perfect maneuvering [1]- [4]. The advancement of this technology encourage to execute the grasping of an object using the electronic vision based gripping (EVBG) mechanism which is mounted on the base of UAV [5] and [6]. The additional capability of this technology to grasp the desired object by utilizing the ''eye in hand'' technology in which camera is equipped on the center of the clutch (gripper), that could increase the gasping efficiency [7] and [8].…”

Section: Introductionmentioning

confidence: 99%

Controlling of an Under-Actuated Quadrotor UAV Equipped With a Manipulator

Ali

2020

IEEE Access

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Unmanned aerial vehicles (UAV) equipped with a manipulator offer an additional flexibility and smart way to grasp the desired objects from inaccessible locations where the access of ground vehicles (GV) are not possible. In this research, we design an adaptive control based regulation, poleplacement and tracking (RST) control scheme for controlling the nonlinear behavior of an under-actuated quad rotor aerial vehicle. The overall performance of the system dealt by MIT rules. The aerial vehicle is equipped with a camera and a gripper that helps us to locate the wanted object from inaccessible location. The model of quad rotor UAV has six degrees of freedom (6-DOF) and the equipped gripper is about (2-DOF). For a successful flight operation UAV requires a reliable controller to stabilize the aerodynamic effects, disturbances that produced by the gripper. Due to aforementioned issue, design an adaptive RST controller, to control the dynamic behavior of the highly nonlinear complex system. Moreover, the effectiveness of the designed controller proven by applying computer-based simulation and it will verify experimentally. Lastly, it observes that the designed controller shows better robustness and good steady state performance to accomplish the given task. INDEX TERMS Adaptive RST controller, UAV with gripper and dual control algorithm, EVBG.

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“…In the area of quadcopter literature, there is a variety of applications as aerial manipulation [1,2], quadcopter pendulum [3], navigation and localization [4,5], obstacle avoidance [6], altitude control [7], and cooperative and formation control [8,9]. Moreover, several control schemes have been proposed including adaptive control [10][11][12][13], fuzzy control [14], neural network control [15], linear parameter varying (LPV) control [16], predictive control [17,18], nonlinear control methods [19][20][21][22][23], and sliding mode control [24,25].…”

Section: Introductionmentioning

confidence: 99%

Advanced UAVs Nonlinear Control Systems and Applications

Joukhadar¹,

Alchehabi²,

Jejeh³

2020

Unmanned Robotic Systems and Applications

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Recent development of different control systems for UAVs has caught the attention of academic and industry, due to the wide range of their applications such as in surveillance, delivery, work assistant, and photography. In addition, arms, grippers, or tethers could be installed to UAVs so that they can assist in constructing, transporting, and carrying payloads. In this book chapter, the control laws of the attitude and position of a quadcopter UAV have been derived basically utilizing three methods including backstepping, sliding mode control, and feedback linearization incorporated with LQI optimal controller. The main contribution of this book chapter would be concluded in the strategy of deriving the control laws of the translational positions of a quadcopter UAV. The control laws for trajectory tracking using the proposed strategies have been validated by simulation using MATLAB ® /Simulink and experimental results obtained from a quadcopter test bench. Simulation results show a comparison between the performances of each of the proposed techniques depending on the nonlinear model of the quadcopter system under investigation; the trajectory tracking has been achieved properly for different types of trajectories, i.e., spiral trajectory, in the presence of unknown disturbances. Moreover, the practical results coincided with the results of the simulation results.

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A review of aerial manipulation of small-scale rotorcraft unmanned robotic systems

Cited by 104 publications

References 48 publications

UAVs’ Formation Keeping Control Based on Multi–Agent System Consensus

UAVs’ Formation Keeping Control Based on Multi–Agent System Consensus

Controlling of an Under-Actuated Quadrotor UAV Equipped With a Manipulator

Advanced UAVs Nonlinear Control Systems and Applications

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