Workspace trajectory control of flexible robot manipulators using neural network and visual sensor feedback

Jiang, Zhaohui

doi:10.1109/ccece.2015.7129503

Cited by 6 publications

(5 citation statements)

References 10 publications

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“…Norman et al [26] used indoor GPS technology to achieve high-accuracy absolute positioning and motion of collaborative robots. Jiang et al [27] developed a visual positioning system which consists of a camera and a video tracker. Susemihl et al [28] proposed a new mobile robot system in order to process large aircraft parts.…”

Section: Literature Review 21 Mobile Intelligent Constructionmentioning

confidence: 99%

Research on Positioning and Simulation Method for Autonomous Mobile Construction Platform

Shi,

Wang,

Phillips

et al. 2024

Buildings

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In the architecture, engineering, and construction (AEC) industry, the positioning technology for a mobile construction platform (MCP) is critical to achieve on-site, continuous, large-scale construction. During construction, MCP movement and construction actions seldom occur simultaneously. Therefore, this paper categorizes the MCP into stationary and moving states for positioning studies, respectively. When the platform is stationary, it is positioned using an improved ultra-wideband (UWB) sensor. When the platform is in motion, a single UWB positioning technique cannot meet the required accuracy for positioning, and fusion positioning using both UWB and an inertial measurement unit (IMU) is considered. The experimental results show that compared with only UWB positioning, the improved UWB positioning algorithm improves the positioning accuracy by 53% in the stationary state, and the fused UWB/IMU positioning improves the positioning accuracy by 46% in the moving state. As a result, the positioning accuracy of the MCP is significantly improved regardless of whether it is in a stationary or moving state. Furthermore, this paper integrates the positioning technique with the robotic arm construction technique to successfully simulate an on-site continuous construction of a wooden cabin, which provides the potential for large-scale continuous construction in real-world scenarios in the future.

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Section: Literature Review 21 Mobile Intelligent Constructionmentioning

confidence: 99%

Research on Positioning and Simulation Method for Autonomous Mobile Construction Platform

Shi,

Wang,

Phillips

et al. 2024

Buildings

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“…Hereby, a collocated output, being the joint angles, is used for the input-output feedback linearization. Also, in [15], end-effector trajectory tracking of a serial robot with two flexible links is performed via computed torque, being a special form of full state feedback linearization, but based only on a rigid-body model. In [4] the theory of a computed torque method for serial flexible link robots is discussed, which only controls the rigid coordinates onto a desired trajectory.…”

Section: Feedback Linearizationmentioning

confidence: 99%

End-effector trajectory tracking of flexible link parallel robots using servo constraints

et al. 2022

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We apply the concept of servo constraints to end-effector trajectory tracking control of parallel robots with structural link flexibilities. Such servo constraints deliver the inverse robot model where solution approaches via projections are proposed, which transform the resulting differential-algebraic equations to ordinary differential equations. The applicable solution process depends on the existence and stability of the internal dynamics. When using the exact end-effector of flexible link robots as output, this internal dynamics is usually unstable. Then a two-point boundary value problem is considered in the framework of stable inversion to obtain the noncausal solution offline. This solution is used as a feedforward control, which is initially combined only with actuator feedback control. To also account for errors within the link flexibility, the well-known linear–quadratic regulator is adapted to end-effector trajectory tracking based on differential-algebraic equations. Finally, we propose a systematic input–output feedback linearization approach, which uses servo constraints for flexible link parallel robots. Here a minimum phase system is obtained by tracking a redefined end-effector output, which is an approximation of the exact end-effector position. All control concepts are validated experimentally with a parallel robot having a highly flexible link. The results allow us to compare different control approaches and show the superior performance of controllers that rely on a flexible multibody model in contrast to classical rigid multibody modeling.

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“…i.e., U (4) i (x i ) − μ € X � 0. Substituting the boundary conditions (11), (15), and (17), we can get the solution of equation (78) that U i (x i ) � 0, which means q � 0. us, the system performance can be asymptotically stabilized with properly choosing the control parameters, leading to the tracking error e i ⟶ 0, u i (x i ) ⟶ 0, and _ u i (x i ) ⟶ 0 as t ⟶ ∞. □…”

Section: Stability Analysismentioning

confidence: 99%

“…us, many researchers focused on using ANN to design an adaptive controller for flexible manipulators in order to track the trajectory error of the payload [14,15]. Besides, other cooperative control strategies interacted with ANN were proposed for control problems of flexible manipulators in previous studies [16], including ANN controllers combined with PID control law [17,18] or sliding mode control law [19,20].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Boundary Control of Flexible Manipulators with Parameter Uncertainty Based on RBF Neural Network

Zhang

Jiang

2020

Shock and Vibration

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In this paper, nonlinear dynamical equations of the flexible manipulator with a lumped payload at the free end are derived from Hamilton's principle. The obtained model consists of both distributed parameters and lumped parameters, namely, partial differential equations (PDEs) governing the flexible motion of links and boundary conditions in the form of ordinary differential equations (ODEs). Considering the great nonlinear approximation ability of the radial basis function (RBF) neural network, we propose a combined control algorithm that includes two parts: one is a boundary controller to track the desired joint positions and suppress the vibration of flexible links; another is a RBF neural network designed to compensate for the parametric uncertainties. The iteration criterion of the RBF neural network weight matrix is derived from the extended Lyapunov function. Stabilization analysis is further carried out theoretically via LaSalle’s invariance principle. Finally, the results of the numerical simulation verify that the proposed control law can realize the asymptotic convergence of tracking error and suppression of the elastic vibration as well.

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Workspace trajectory control of flexible robot manipulators using neural network and visual sensor feedback

Cited by 6 publications

References 10 publications

Research on Positioning and Simulation Method for Autonomous Mobile Construction Platform

Research on Positioning and Simulation Method for Autonomous Mobile Construction Platform

End-effector trajectory tracking of flexible link parallel robots using servo constraints

Adaptive Boundary Control of Flexible Manipulators with Parameter Uncertainty Based on RBF Neural Network

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