Hybrid Control Strategy for Force and Precise End Effector Positioning of a Twisted String Actuator

Rodriguez, Andres; Hosseini, Mohssen; Paik, Jamie

doi:10.1109/tmech.2020.3047157

Cited by 17 publications

(7 citation statements)

References 32 publications

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“…Corollary 1: If s h (x) converges to 0 1×p for all x ∈ X , Z 2 ( x) tends to be a deterministic function. In this case the model (8) converges to the GP model (7).…”

Section: A Nested Gaussian Process Modelsmentioning

confidence: 98%

“…In the mechatronics field, Rodriguez et al developed one hybrid control scheme with two nested loops for twisted string actuators [7]. Nested design techniques have been used for codesign of controlled systems [8].…”

Section: B Literature Reviewmentioning

confidence: 99%

“…Corollary 1 shows that the NGP model ( 6) can be approximated by the GP model (7), if s h (x) is small for all x ∈ X . It relaxes the condition for an NGP model able to be approximated by a GP model in Theorem 1.…”

Section: A Nested Gaussian Process Modelsmentioning

confidence: 99%

“…Then, K-fold cross-validation method is used to exam whether the NGP is a GP or not. More specifically, build GP model (7) to approximate the nested computer outputs and then examine the prediction accuracy of this GP model by K-fold crossvalidation method. Here, choice of K follows the criterion below [39] K ≈ log(n) and n/K > 3d.…”

mentioning

confidence: 99%

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Nested Bayesian Optimization for Computer Experiments

Wang

AlBahar

et al. 2023

IEEE/ASME Trans. Mechatron.

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Computer experiments can emulate the physical systems, help computational investigations, and yield analytic solutions. They have been widely employed with many engineering applications (e.g., aerospace, automotive, energy systems). Conventional Bayesian optimization did not incorporate the nested structures in computer experiments. This paper proposes a novel nested Bayesian optimization method for complex computer experiments with multi-step or hierarchical characteristics. We prove the theoretical properties of nested outputs given that the distribution of nested outputs is Gaussian or non-Gaussian. The closed forms of nested expected improvement are derived. We also propose the computational algorithms for nested Bayesian optimization. Three numerical studies show that the proposed nested Bayesian optimization method outperforms the five benchmark Bayesian optimization methods that ignore the intermediate outputs of the inner computer code. The case study shows that the nested Bayesian optimization can efficiently minimize the residual stress during composite structures assembly and avoid convergence to local optima.

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“…Corollary 1: If s h (x) converges to 0 1×p for all x ∈ X , Z 2 ( x) tends to be a deterministic function. In this case the model (8) converges to the GP model (7).…”

Section: A Nested Gaussian Process Modelsmentioning

confidence: 98%

Section: B Literature Reviewmentioning

confidence: 99%

Section: A Nested Gaussian Process Modelsmentioning

confidence: 99%

mentioning

confidence: 99%

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Nested Bayesian Optimization for Computer Experiments

Wang

AlBahar

et al. 2023

IEEE/ASME Trans. Mechatron.

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“…End-effector functions, which can be monitored or be controlled, are the gripping force and movement, speed, position, and orientation of the object, forces, and movement during manipulation, identification of contact point, and so on. Extensive details regarding end-effector control strategies can be found in [12,26,43].…”

Section: Additional Sensorsmentioning

confidence: 99%

An Overview of End Effectors in Agricultural Robotic Harvesting Systems

et al. 2022

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In recent years, the agricultural sector has turned to robotic automation to deal with the growing demand for food. Harvesting fruits and vegetables is the most labor-intensive and time-consuming among the main agricultural tasks. However, seasonal labor shortage of experienced workers results in low efficiency of harvesting, food losses, and quality deterioration. Therefore, research efforts focus on the automation of manual harvesting operations. Robotic manipulation of delicate products in unstructured environments is challenging. The development of suitable end effectors that meet manipulation requirements is necessary. To that end, this work reviews the state-of-the-art robotic end effectors for harvesting applications. Detachment methods, types of end effectors, and additional sensors are discussed. Performance measures are included to evaluate technologies and determine optimal end effectors for specific crops. Challenges and potential future trends of end effectors in agricultural robotic systems are reported. Research has shown that contact-grasping grippers for fruit holding are the most common type of end effectors. Furthermore, most research is concerned with tomato, apple, and sweet pepper harvesting applications. This work can be used as a guide for up-to-date technology for the selection of suitable end effectors for harvesting robots.

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A Compound Controller for Twisted String Actuator System

Wei

Liu

2022

Proceedings of the Eighth Asia International Symposium on Mechatronics

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Hybrid Control Strategy for Force and Precise End Effector Positioning of a Twisted String Actuator

Cited by 17 publications

References 32 publications

Nested Bayesian Optimization for Computer Experiments

Nested Bayesian Optimization for Computer Experiments

An Overview of End Effectors in Agricultural Robotic Harvesting Systems

A Compound Controller for Twisted String Actuator System

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