Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured **...
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Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.
In this paper, the effect of the initial state of the drilling system on trajectory tracking is taken into account in the directional drilling trajectory tracking control. Firstly, the trajectory model describing the ...
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ISBN:
(数字)9789887581598
ISBN:
(纸本)9798331540845
In this paper, the effect of the initial state of the drilling system on trajectory tracking is taken into account in the directional drilling trajectory tracking control. Firstly, the trajectory model describing the two-dimensional drilling trajectory of the rotary steering system (RSS) is introduced. To improve the accuracy of trajectory tracking control and reduce the trajectory deviation, a fixed-time sliding mode control (FTSMC) method is introduced. Then, the stability of the closed-loop system is analyzed, and the range of controller parameters satisfying the stability condition is obtained. Finally, the effectiveness of the designed control strategy is verified by simulation experiments.
Aerial-underwater vehicles present control challenges in both aerial and underwater environments, so obtaining a model for simulating the current effects experienced by these vehicles in both environments provides an ...
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ISBN:
(数字)9798350391084
ISBN:
(纸本)9798350391091
Aerial-underwater vehicles present control challenges in both aerial and underwater environments, so obtaining a model for simulating the current effects experienced by these vehicles in both environments provides an important theoretical basis for analyzing dynamic behavior in closed-loop control. This article proposes the analysis of an aerial-underwater hybrid vehicle while adding the effects of ocean currents as perturbations. In this regard, it is intended to explore two numerical simulation scenarios: in the first scenario, the vehicle performs a mission in an underwater environment without the presence of ocean currents, and in the second scenario, with the inclusion of the effect of ocean currents under the same mission conditions, to illustrate the difference in the vehicle's behavior.
As a part of the circular economy - which aims at closing the loop of materials - remanufacturing is getting more and more attention in recent years. With remanufacturing, companies are carrying out a recovery operati...
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With the increasing deployment of renewable energy-based power generation plants,the power system is becoming increasingly vulnerable due to the intermittent nature of renewable energy,and a blackout can be the worst ...
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With the increasing deployment of renewable energy-based power generation plants,the power system is becoming increasingly vulnerable due to the intermittent nature of renewable energy,and a blackout can be the worst *** current auxiliary generators must be upgraded to energy sources with substantially high power and storage capacity,a short response time,good profitability,and minimal environmental *** in the power restoration of renewable energy generators should also be *** different energy storage methods can store and release electrical/thermal/mechanical energy and provide flexibility and stability to the power ***,a review of the use of energy storage methods for black start services is provided,for which little has been discussed in the ***,the challenges that impede a stable,environmentally friendly,and cost-effective energy storage-based black start are *** energy storagebased black start service may lack supply ***,the typical energy storage-based black start service,including explanations on its steps and configurations,is *** start services with different energy storage technologies,including electrochemical,thermal,and electromechanical resources,are *** suggest that hybridization of energy storage technologies should be developed,which mitigates the disadvantages of individual energy storage methods,considering the deployment of energy storage-based black start services.
Traditional electroencephalograph(EEG)-based emotion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer i...
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Traditional electroencephalograph(EEG)-based emotion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer interface(BCI)in *** attempt to use the multi-modal data from the past session to realize emotion recognition in the case of a small amount of calibration *** solve this problem,we propose a multimodal domain adaptive variational autoencoder(MMDA-VAE)method,which learns shared cross-domain latent representations of the multi-modal *** method builds a multi-modal variational autoencoder(MVAE)to project the data of multiple modalities into a common *** adversarial learning and cycle-consistency regularization,our method can reduce the distribution difference of each domain on the shared latent representation layer and realize the transfer of *** experiments are conducted on two public datasets,SEED and SEED-IV,and the results show the superiority of our proposed *** work can effectively improve the performance of emotion recognition with a small amount of labelled multi-modal data.
During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintain...
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ISBN:
(数字)9798350368604
ISBN:
(纸本)9798350368611
During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust $H_{\infty}$ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller's effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction.
This paper studies the problem of trajectory tracking control for directional drilling in underground coal mine by devising a robust model predictive control method. First, a directional drilling trajectory extension ...
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ISBN:
(数字)9798331521950
ISBN:
(纸本)9798331521967
This paper studies the problem of trajectory tracking control for directional drilling in underground coal mine by devising a robust model predictive control method. First, a directional drilling trajectory extension model is obtained by the linearization of a drilling tool kinematic model through the Taylor series expansion in the borehole depth domain. Then, in view of the influence of the uncertainty of the drilling tool slope and external interference, a robust model predictive control method is introduced in the form of an optimal control problem. A sufficient condition is obtained to calculate the corresponding controller gain matrix on the premise of satisfying the stability of the closedloop control system and the $H_{\infty}$ performance index. At last, the effectiveness of our method is illustrated through simulation analysis. Compared with model predictive control, robust model predictive control directly incorporates the uncertainty of the drilling tool slope and external interference into the control design, enabling it to better adapt to the complex and variable underground coal mine environment.
Several coffee producers rely on manual inspection for quality control, which is prone to inconsistencies and time consumption. Recent studies have proposed Comparison performance on State-of-The-Art (SOTA). Deep lear...
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ISBN:
(数字)9789887581598
ISBN:
(纸本)9798331540845
Several coffee producers rely on manual inspection for quality control, which is prone to inconsistencies and time consumption. Recent studies have proposed Comparison performance on State-of-The-Art (SOTA). Deep learning models were investigated as part of the proposed intelligent computer vision for faster and more reliable coffee bean grading. Performance Deep learning models, i.e., MobileNetV3Small, ResNet50, EfficientNetV2L, and DenseNet201, were evaluated to grade the quality of coffee beans that followed a grading procedure based on Indonesian National Standard (SNI) 01-2907-2008. A specific tray was designed to position coffee beans evenly without overlap for sample preparation, which consist of about 500–600 coffee beans. The process of capturing images is conducted systematically, focusing on each type of coffee bean defect individually. For comparison of SOTA models, five classes of coffee bean defects, With 1053 beans per class, the total dataset comprises 5265 beans. This dataset was divided into 10% for testing and 90% for training. Within the training data, 12% was reserved for validation. The result from this paper shows that MobileNetV3Small achieves the highest accuracy (99.43%) with minimal memory and parameters. Its efficient design allows for robust feature extraction, crucial for distinguishing subtle defect features. While larger models like ResNet50 and EfficientNetV2L also perform well, they exhibit higher memory and parameters.
Length variation of heavy plate after cooling bed is hard to calculate accurately because of large size, uneven temperature and material property. The thermal expansion coefficient is not consistent even the same stee...
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