Indirect adaptive control of an autonomous underwater vehicle-manipulator system for underwater manipulation tasks

Mohan, Santhakumar; Kim, Jinwhan

doi:10.1016/j.oceaneng.2012.07.022

Cited by 112 publications

(29 citation statements)

References 12 publications

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“…(10) represents the force and the moment between two adjacent links including the hydrodynamic effects. 2,3 (10) where R is the rotation matrix from the subscript coordinate system to the superscript coordinate system; f i and t i represent the resultant force and moment vector at the i-th joint respectively; d is the position vector from the origin of former coordinate system to that of latter coordinate system; b, P and H denote the buoyancy, hydrodynamic forces and moments acting on the link respectively.…”

Section: Dynamics Of Underwater Manipulatormentioning

confidence: 99%

Trajectory generation and sliding-mode controller design of an underwater vehicle-manipulator system with redundancy

Kim

Choi

Kim

et al. 2015

Int. J. Precis. Eng. Manuf.

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An Underwater Vehicle-Manipulator System (UVMS) can be applied to pick up and carry objects for autonomous manipulation in the water. However, it is difficult to control the motion of the whole system because the movement of a manipulator affects the motion of the vehicle and vice versa. Additionally, a lack of information about the object, such as the shape and inertia, makes motion control even more difficult. In the current paper, a motion control algorithm of the UVMS with redundancy was developed to guarantee the stability robustness when the mass information of the objects is not available. In order to generate the joint trajectories of the manipulator, a redundancy resolution was performed to minimize the restoring moments acting on the vehicle. This means the propulsion energy for controlling the vehicle's motion can be reduced. To control the motion of the system with an unknown parameter, a controller based on the sliding mode theory has been designed. Finally, the effectiveness of the proposed method was verified through a series of simulation for a 3DOF vehicle-3DOF manipulator system.

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Section: Dynamics Of Underwater Manipulatormentioning

confidence: 99%

Trajectory generation and sliding-mode controller design of an underwater vehicle-manipulator system with redundancy

Kim

Choi

Kim

et al. 2015

Int. J. Precis. Eng. Manuf.

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“…그림 3의 수중 로봇 팔은 PETASUS 시스템의 링키지 형태의 5자유도 로봇 팔이 그대로 사용되었다 [4] . 다만 DSP 보드와 CAN을 통해 이루어지던 통신 및 제어는 Maxon motor 사의 EPOS 2 모델로 교체되었으며, USB를 통해 3.1 위치 인식 시스템 [5,11] 수조 …”

Section: 수중 로봇 팔 Pumunclassified

Localization and Autonomous Control of PETASUS System II for Manipulation in Structured Environment

Han¹,

Ok²,

Chung³

2013

The Journal of Korea Robotics Society

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In this paper, a localization algorithm and an autonomous controller for PETASUS system II which is an underwater vehicle-manipulator system, are proposed. To estimate its position and to identify manipulation targets in a structured environment, a multi-rate extended Kalman filter is developed, where map information and data from inertial sensors, sonar sensors, and vision sensors are used. In addition, a three layered control structure is proposed as a controller for autonomy. By this controller, PETASUS system II is able to generate waypoints and make decisions on its own behaviors. Experiment results are provided for verifying proposed algorithms.

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“…Different from the above nonlinear systems, underwater vehicles operate relatively slowly in the complex ocean environment, suffering from ocean current disturbance inevitably. Besides, due to the inherent nonlinearity and serious multivariate coupling, it leads to a large uncertainty in the model of underwater vehicle based on dynamic modeling theory [21][22][23][24]. Therefore, the external disturbance and modeling uncertainty result in fault tolerant control more complicated for underwater vehicles [22,23].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, due to the inherent nonlinearity and serious multivariate coupling, it leads to a large uncertainty in the model of underwater vehicle based on dynamic modeling theory [21][22][23][24]. Therefore, the external disturbance and modeling uncertainty result in fault tolerant control more complicated for underwater vehicles [22,23]. And during the operation of underwater vehicle, it is difficult to estimate the upper bounds of external disturbance and modeling uncertainty in advance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive terminal sliding mode based thruster fault tolerant control for underwater vehicle in time-varying ocean currents

Zhang

Liu

Yin

et al. 2015

Journal of the Franklin Institute

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Indirect adaptive control of an autonomous underwater vehicle-manipulator system for underwater manipulation tasks

Cited by 112 publications

References 12 publications

Trajectory generation and sliding-mode controller design of an underwater vehicle-manipulator system with redundancy

Trajectory generation and sliding-mode controller design of an underwater vehicle-manipulator system with redundancy

Localization and Autonomous Control of PETASUS System II for Manipulation in Structured Environment

Adaptive terminal sliding mode based thruster fault tolerant control for underwater vehicle in time-varying ocean currents

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