Performance analysis of 3 DOF Delta parallel robot

Stan, Sergiu-Dan; Manic, Milos; Szep, Cristian; Bălan, Radu

doi:10.1109/hsi.2011.5937369

Cited by 36 publications

(21 citation statements)

References 21 publications

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“…Average of the position error for l 1 /l 2 /l 3 (mm) 0.023/À0.015/0.008 0.045/0.037/À0.018 Maximum of the position error for l 1 /l 2 /l 3 …”

Section: Numerical Model Neural Network Modelmentioning

confidence: 99%

“…Compared with the conventional serial mechanisms, parallel mechanisms have potential advantages in accuracy, dynamics, and stiffness. Hundreds of robots using parallel mechanisms have been developed and analyzed, such as the Stewart platform, 1,2 Delta robot, 3 and Tricept robot. 4,5 However, the practical parallel robots show gaps between the expected and actual performances.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of numerical and neural network methods for the kinematic modeling of a hybrid structure robot

Kang

Chanal

Dai

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part C:

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A combination of parallel and serial mechanisms allows for stiff and dexterous motion of the robotic end-effector but increases the complexity of the kinematic problem. Many of the geometric parameters for such robots are difficult to obtain. This paper presents the numerical and neural network methods to solve the kinematics for such a hybrid robot named Exechon Õ . Both methods avoid the geometric measurement in the real robot. The geometric parameters used in the numerical model are identified by a particle swarm optimization algorithm. At the same time, a radial basis functionbased neural network is trained to approximate the kinematics of the Exechon robot. The resultant models are then compared in terms of modeling accuracy and real-time ability. The presented methods are generic and can be applied to other robots with similar structures.

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“…Average of the position error for l 1 /l 2 /l 3 (mm) 0.023/À0.015/0.008 0.045/0.037/À0.018 Maximum of the position error for l 1 /l 2 /l 3 …”

Section: Numerical Model Neural Network Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of numerical and neural network methods for the kinematic modeling of a hybrid structure robot

Kang

Chanal

Dai

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part C:

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show abstract

“…A method for finding the workspace can be found with the help of Andrioaia et al (2012). It is possible to design a TAC based on workspace requirements (Stan et al, 2011) but this will not be treated in this paper.…”

Section: Workpacementioning

confidence: 99%

Three-axis Motion Compensated Crane Head Control**This work has been carried out at the Centre for Autonomous Marine Operations and Systems (NTNU AMOS). The Norwegian Research Council is acknowledged as the main sponsor of NTNU AMOS. This work was supported by Ulstein Power & Control AS and the Research Council of Norway, Project number 241205.

et al. 2016

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Offshore operations can be harsh and demanding and set personnel and equipment at risk. Ships will be exposed to the elemental forces of wind, waves and current, which will influence offshore crane operations considerably. This paper addresses the use of a crane head, constructed as a Delta parallel robot, to compensate for the motions of the ship in three axes. This type of robot has a rigid and accurate structure, but because of its highly nonlinear nature, advanced control algorithms must be derived. This paper includes both forward and inverse kinematics for the robot, as well as velocity kinematics and workspace analysis. The kinematics of a full crane system, with the robot as its head, has been modelled, and a simulator which includes a model of a supply vessel is created. The disturbances on the system from the elements are translated and rotated to the crane head frame of reference for use in the compensation procedure. PID controllers are used to control the crane head, and simulations are conducted to verify that the crane head is able to compensate for the motions created by waves.

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“…The stiffness matrix can be obtained from the kinematics equations and is given by (16) where k is a scalar representing the stiffness of each actuator (modelled as a linear spring), while J is the Jacobian matrix. The stiffness matrix is a positive semidefinite matrix; see [11] [12][1] [13].…”

Section: Stiffnessmentioning

confidence: 99%

Workspace and Payload-Capacity of a New Reconfigurable Delta Parallel Robot

Maya

Castillo²,

Lomelí

et al. 2013

International Journal of Advanced Robotic Systems

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In this paper the workspace and payload capacity of a new design of reconfigurable Delta-type parallel robot is analysed. The reconfiguration is achieved by adjusting the length of the kinematic chains of a given robot link simultaneously and symmetrically during the operation of the robot. This would produce a dynamic workspace in shape and volume. A numerical analysis of the variation of shape and volume of the workspace and payload capacity of the robot is presented. Based both on the results of this analysis and on practical requirements, a proposal for the design of a reconfiguring mechanism is presented.

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Performance analysis of 3 DOF Delta parallel robot

Cited by 36 publications

References 21 publications

Comparison of numerical and neural network methods for the kinematic modeling of a hybrid structure robot

Comparison of numerical and neural network methods for the kinematic modeling of a hybrid structure robot

Workspace and Payload-Capacity of a New Reconfigurable Delta Parallel Robot

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