Hierarchical control of aerial manipulation vehicle

Kannan, Somasundar; Bezzaoucha, Souad; Guzman, Serket Quintanar; Dentler, Jan; Olivares-Méndez, Miguel A.; Voos, Holger

doi:10.1063/1.4972661

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…r in control laws (26), (33) and (36), the compensation of the Centrifugal and Coriolis terms, C, has been neglected; r an aerodynamic disturbance, acting on the vehicle vessel from time t w = 20 s, has been considered and modeled as 46…”

Section: Gainmentioning

confidence: 99%

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An adaptive hierarchical control for aerial manipulators

Pierri¹,

Muscio²,

Caccavale³

2018

Robotica

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SUMMARYThis paper addresses the trajectory tracking control problem for a quadrotor aerial vehicle, equipped with a robotic manipulator (aerial manipulator). The controller is organized in two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the upper layer. To the purpose, a model-based control scheme is adopted, where modelling uncertainties are compensated through an adaptive term. The stability of the proposed scheme is proven by resorting to Lyapunov arguments. Finally, a simulation case study is proposed to prove the effectiveness of the approach.

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Section: Gainmentioning

confidence: 99%

“…Hierarchical control of aerial manipulators to perform tasks in operational space has been introduced in [25], where a model-based control approach is pursued, and in [26], where model-free motion control laws are adopted. The algorithm in [25] has been extended via an adaptive term for compensating the model uncertainties.…”

Section: Introductionmentioning

confidence: 99%

An adaptive hierarchical control for aerial manipulators

Pierri¹,

Muscio²,

Caccavale³

2018

Robotica

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“…The literature lists many control strategies for aerial manipulation. For instance, a Hierarchical Control of Aerial Manipulation Vehicle using PID controller in operational space is presented in Kannan et al (2017), when in Orsag et al (2013) a model reference adaptive control is proposed for a light-weight prototype three-arm manipulator, each arm with 2 Dofs. While an adaptive hierarchical control to compensate uncertain modelling is presented in Pierri et al (2018).…”

Section: Introductionmentioning

confidence: 99%

Combined algorithms for analytical inverse kinematics solving and control of the Q-PRR aerial manipulator*

Bouzgou

Benchikh

Nouvelière

et al. 2022

Mechanics Based Design of Structures and Machines

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This paper presents the design and modeling of a new aerial manipulator system, called Q-PRR, composed of three joints with a fixed base in the center of mass of the multirotor considered as a whole system. This structure has a prismatic joint as a first joint which allows to keep the center of gravity of the Q-PRR as close as possible to the center of gravity of the multirotor. This will also allow to reduce the influence of arm motion on the multirotor roll thus to ensure the stability of the system on trajectory tracking with dynamic changes in the multirotor's center of gravity. Furthermore, the configuration of the manipulator arm for the desired position of the end-effector given by the inverse kinematics model is kept without any change in the position and attitude of the multirotor. This paper develops both forward and inverse kinematics models for a nonlinear underactuated system using the Denavit-Hartenberg notation. When a new algorithm is presented for the inverse kinematics based on Levenberg-Marquardt algorithm. Then, the dynamic model in the joint spaces is developed with the Lagrangian formalism. The Q-PRR is controlled using a model-free control with a comparison of two states, a free fly and disturbance forces applied to the whole system with manipulator arm movement.

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Hierarchical control of aerial manipulation vehicle

Cited by 2 publications

References 11 publications

An adaptive hierarchical control for aerial manipulators

An adaptive hierarchical control for aerial manipulators

Combined algorithms for analytical inverse kinematics solving and control of the Q-PRR aerial manipulator*

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