In this paper,we propose a fully Soft Bionic Grasping Device(SBGD),which has advantages in automatically adjusting the grasping range,variable stiffness,and controllable bending *** device consists of soft gripper str...
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In this paper,we propose a fully Soft Bionic Grasping Device(SBGD),which has advantages in automatically adjusting the grasping range,variable stiffness,and controllable bending *** device consists of soft gripper structures and a soft bionic bracket *** adopt the local thin-walled design in the soft gripper *** design improves the grippers’bending efficiency,and imitate human finger’s segmental bending *** addition,this work also proposes a pneumatic soft bionic bracket structure,which not only can fix grippers,but also can automatically adjust the grasping space by imitating the human adjacent fingers’opening and closing *** to the above advantages,the SBGD can grasp larger or smaller objects than the regular grasping ***,to grasp small objects reliably,we further present a new Pinching Grasping(PG)*** great performance of the fully SBGD is verified by *** work will promote innovative development of the soft bionic grasping robots,and greatly meet the applications of dexterous grasping multi-size and multi-shape objects.
Image segmentation has impressive progress in the past several *** good segmentation usually follows pixelwise well-annotated labels which is ***,the robustness would not be guaranteed due to lack-ofdiversity *** work...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Image segmentation has impressive progress in the past several *** good segmentation usually follows pixelwise well-annotated labels which is ***,the robustness would not be guaranteed due to lack-ofdiversity *** work usually focuses on pixels individually and pay less attention to the neighbor *** local context would be scarce and the global context is not utilized following these *** proposal a method,named Forest Semantic Segmentation Network(FSSNet) to address these *** organizes original version and augmented version of images,as two inputs into student branch and teacher branch,and force the two outputs being consistent to strengthen the robustness of our ***,we not only consider pixel itself and also the neighbor pixels because the context of neighbor pixels helps understanding the *** utilizes contrastive loss with memory bank to involve global context in training which will make pixels closer to others in same category and far away from pixels of different categories.A bank filter is suggested to improve the quality of features in the memory *** also proposal a new sample strategy to improve the effect of contrastive loss and reduce the *** method can improve accuracy and strengthen the robustness with affordable extra computation during training process,and no additional computation during inference toward *** to benchmark,the proposed approach can improve the mIoU by 3.1% on our challenging dataset.
It is a key challenge for soft grasping devices to stably grasp unstructured objects with multi-size and multi-shape. The conventional single-function grippers have some limitations in grasping the above kinds of obje...
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It is a key challenge for soft grasping devices to stably grasp unstructured objects with multi-size and multi-shape. The conventional single-function grippers have some limitations in grasping the above kinds of objects. This work proposes a modular four-modal soft grasping device(MFSGD), which consists of soft fingers, suction cups, soft wrapper, and other structures. It can perform a variety of grasping modes such as bending grasping mode, wrapping grasping mode, end liftingsucking mode, and side fixed-sucking mode. It may be one of the devices with the most grasping modes at present. Moreover, the device adopts a fully modular design with different structures connected by magnets. It is not only convenient to disassemble or assemble, so as to solve the mutual interference of different modal structures problem during grasping, but also simplifies the fabrication of the multi-modal grasping device. In addition, this work matches the suitable grasping modes for objects of different shapes and sizes, and obtains the relative characteristics of the MFSGD. The proposed device can improve the ability of the grasping robots, and is expected to play an important role in economic and industrial fields.
Small object detection in the cigarette detection field is a recent popular task. As cigarette targets in surveillance are tiny, the object scale leads to a great challenge of object detection. To solve the issue ment...
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This paper investigates the containment problem of continuous-time multi-agent systems with multiplicative noises,where the first-order and second-order multi-agent systems are studied *** on stochastic analysis tools...
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This paper investigates the containment problem of continuous-time multi-agent systems with multiplicative noises,where the first-order and second-order multi-agent systems are studied *** on stochastic analysis tools,algebraic graph theory,and Lyapunov function method,the containment protocols based the relative states measurement with multiplicative noises are developed to guarantee the mean square and almost sure ***,the sufficient conditions and necessary conditions related to the control gains are derived for achieving mean square and almost sure *** is also shown that multiplicative noises may works positively for the almost sure containment of the first-order multi-agent *** examples are also introduced to illustrate the effectiveness of the theoretical results.
A Multimodal Emotion Perception model with Audio and Visual modalities(MEP-AV) is proposed to detect the individual emotions in public *** framework of MEP-AV model consists of four parts,i.e.,data collection module,a...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
A Multimodal Emotion Perception model with Audio and Visual modalities(MEP-AV) is proposed to detect the individual emotions in public *** framework of MEP-AV model consists of four parts,i.e.,data collection module,audio expression analysis module,visual expression analysis module and multimodal fusion *** order to ensure that the emotion perception results meet the requirement of short-term continuity,a Context-Aware Decision-Level Fusion(CADLF) model is proposed and applied in multimodal fusion *** CADLF model estimates the affective status by using context information of multimodal *** short-term continuity is considered to improve the accuracy of the emotion perception *** experiment results evaluated by various metrics demonstrate that the performance of the multimodal structure is improved compared with that of unimodal emotion *** MEP-AV model using multimodal fusion algorithm provides the accuracies of70.89% and 77.07% in valence and arousal *** F1-scores reaches 70.2% and 75.6% respectively,indicating the boost performance on emotion perception.
The evaluation of regional geological hazard susceptibility is of great significance to the prevention and control of geological hazard. In this paper, the "4-20"Lushan earthquake disaster area as the resear...
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This paper is aimed at the second-order linear multi-agent formation *** to the failure of the actuator in a node,the wrong interactive information is transmitted between nodes,so that the entire system cannot complet...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
This paper is aimed at the second-order linear multi-agent formation *** to the failure of the actuator in a node,the wrong interactive information is transmitted between nodes,so that the entire system cannot complete the expected task.A distributed adaptive fault isolation and fault tolerance method based on consistency theory is *** the consistency error variable is designed according to the connection relationship between nodes and the faulty node,which eliminates the influence of the faulty node on the neighbor ***,an overall distributed adaptive fault isolation and fault tolerance approach is designed according to the local information of neighbor *** stability of the designed approach is proved by constructing a reasonable Lyapunov *** results show that the proposed adaptive control approach has good robustness.
Model predictive current control(MPCC) is widely applied in electrical drives and power electronics because of its simplicity and ***,steady-state errors are always present because of the inaccurate prediction induced...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Model predictive current control(MPCC) is widely applied in electrical drives and power electronics because of its simplicity and ***,steady-state errors are always present because of the inaccurate prediction induced by changing actual *** paper proposes a simple strategy for improving MPCC performance,which reduces steadystate errors and eliminates the additional prediction *** cost function,which is made up of tracking mistakes,is used in MPCC to choose the best switching *** paper introduces a new cost function that also includes actual current *** is a coefficient of actual current errors that enhances the appropriateness of permanent magnet synchronous motor(PMSM) *** results show superior performance of the proposed MPCC to that of conventional MPCC.
The inter-class similarity of facial expressions is one of the key challenges in Facial Expression Recognition(FER).In this manuscript,a Latent Facial Action Units Network(LAUNet) is proposed for the problem of inter-...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
The inter-class similarity of facial expressions is one of the key challenges in Facial Expression Recognition(FER).In this manuscript,a Latent Facial Action Units Network(LAUNet) is proposed for the problem of inter-class similarity of facial expressions in *** proposed method recognizes subtle differences between facial expressions by learning Latent Facial Action Units Features(LAUFs).Specifically,LAUNet is composed of two parts:the Latent Facial Action Units Features Extraction Network(LEN) and the Latent Facial Action Units Selection Network(LSN).Firstly,LEN extracts LAUFs from the feature map of the backbone using the spatial attention ***,taking advantage of the channel attention mechanism,LSN captures the latent relationships between features from LAUFs to select effective features for *** are performed on the dataset after removing the invalid data of non-face images from the original FER2013 *** with some previous state-of-the-art methods,LAUNet achieves the highest accuracy rate of 71.31%.Depending on the backbone,LAUNet can improve the accuracy by up to 5.46% compared to the original architecture of the backbone.
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