Modified Linear Technique for the Controllability and Observability of Robotic Arms

Rubio, José de Jesús; Orozco, Eduardo; Cordova, Daniel Andres; Islas, Marco Antonio; Pacheco, Jaime; Gutiérrez, Guadalupe Juliana; Zacarías, Alejandro; Soriano, Luis Arturo; Meda-Campaña, J. A.; Mújica-Vargas, Dante

doi:10.1109/access.2021.3140160

Cited by 49 publications

(8 citation statements)

References 43 publications

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“…Compared to humans, designed manipulators have many benefits including high adaptability, high accuracy, low-production cost, and low-error rate. However, in practice, manipulators have varying parameter inaccuracies compared to their underlying theoretical models [1][2][3][4][5][6]. These discrepancies are due to a host of reasons, including tolerance design, machining errors, assembly errors, and mechanical wear [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Kinematic calibration and feedforward control of a heavy-load manipulator using parameters optimization by an ant colony algorithm

Wang,

Xie,

Jiang

et al. 2024

Robotica

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Most of the currently available three-degree-of-freedom manipulators are light load and cannot achieve full continuous rotation; given this, we designed a heavy-load manipulator that achieves unrestricted and continuous rotation. Due to manufacturing and assembly errors, parameter deviations between the real manipulator and its underlying theoretical model were unavoidable. Because of the lack of high-precision, high-frequency, and real-time closed-loop detection methods, we proposed a type of kinematics calibration of parameterized ant colony optimization and feedforward control methods. This was done to achieve high-precision motion control. First, an error model combining structural parameters and joint output angles was established, and the global sensitivity of each error source was analyzed to distinguish both primary and secondary sources. Based on the measured data of a laser tracker, the ant colony optimization was then used to identify six error sources. This resulted in both link length and joint driving errors of the designed manipulator. As it is a type of systematic error, the rounding error of the theoretical trajectory was carefully analyzed, and feedforward control methods with different coefficients were designed to further improve positioning accuracy based on the kinematic calibration. Experimental results showed that the proposed kinematic calibration and feedforward control methods achieved relatively precise motion control for the designed manipulator.

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Section: Introductionmentioning

confidence: 99%

Kinematic calibration and feedforward control of a heavy-load manipulator using parameters optimization by an ant colony algorithm

Wang,

Xie,

Jiang

et al. 2024

Robotica

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show abstract

“…The unreachable optimal configuration of the camera is mainly caused by the head rotation. Therefore, the tracking algorithm should increase the weights of the orientation control object [15][16][17][18][19][20]. Furthermore, a patient's head always rotates from side to side because the body is constrained on the bed.…”

Section: Introductionmentioning

confidence: 99%

Face-tracking algorithm for large-amplitude head motions with a 7-DOF manipulator

et al. 2023

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The collection of facial action data is essential for the accurate evaluation of a patient’s condition in the intensive care unit, such as pain evaluation. An automatic face-tracking system is demanded to reduce the burden of data collection on the medical staff. However, many previous studies assume that the optimal trajectory of a robotic tracking system is reachable which is inapplicable for large-amplitude head motions. To tackle this problem, we propose a region-based face-tracking algorithm for large-amplitude head motion with a 7-DOF manipulator. A configuration-based optimization algorithm is proposed to trade-off between theoretical optimal pose and workspace constraints through the assignment of importance weights. To increase the probability of recapturing the face exceeding the reachable workspace of the manipulator, the camera is directed toward the center of the head, named the facial orientation center (FOC) constraint. Furthermore, a region-based tracking approach is designed to stabilize the manipulator for small amplitude head motions and smooth the tracking trajectory by adjusting the joint angle in the null space of the 7-DOF manipulator. Experimental results demonstrate the effectiveness of the proposed algorithm in tracking performance and finding an appropriate configuration for the unreachable theoretical optimal configuration. Moreover, the proposed algorithm with FOC constraint can successfully follow the head motion as losing 33.2% of the face during the tracking.

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“…Designing a robust controller for uncertain systems that can accommodate such uncertainties has always been an important yet challenging problem. To retain the robustness property, various robust control methods have been developed against model uncertainties [3][4][5][6][7][8]. Conventional robust control methods, however, were studied mainly via offline means.…”

Section: Introductionmentioning

confidence: 99%

Robust Trajectory Tracking of Uncertain Systems via Adaptive Critic Learning

2022

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This study develops an adaptive dynamic programming (ADP) scheme for uncertain systems to achieve the robust trajectory tracking. In this framework, the augmented state is first established via combining the tracking error and reference trajectory, where the robust tracking control problem can be resolved using the regulation control strategy. Then, the robust control problem of uncertain system can be represented as an optimal control problem of nominal system, which provides a new pathway to address the robust control problem. To realize the optimal control, the derived Hamilton–Jacobi–Bellman equation (HJBE) is solved by training a critic neural network (CNN). Finally, two innovative critic learning techniques are suggested to calculate the unknown NN weights, where the convergence of NN weights can be guaranteed. Simulations are carried out to demonstrate the effectiveness of the proposed method.

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Modified Linear Technique for the Controllability and Observability of Robotic Arms

Cited by 49 publications

References 43 publications

Kinematic calibration and feedforward control of a heavy-load manipulator using parameters optimization by an ant colony algorithm

Kinematic calibration and feedforward control of a heavy-load manipulator using parameters optimization by an ant colony algorithm

Face-tracking algorithm for large-amplitude head motions with a 7-DOF manipulator

Robust Trajectory Tracking of Uncertain Systems via Adaptive Critic Learning

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