The increase in precision agriculture has promoted the development of picking robottechnology,and the visual recognition system at its core is crucial for improving the level of agricultural *** paper reviews the pro...
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The increase in precision agriculture has promoted the development of picking robottechnology,and the visual recognition system at its core is crucial for improving the level of agricultural *** paper reviews the progress of visual recognition tech-nology for picking robots,including image capture technology,target detection algorithms,spatial positioning strategies and scene *** article begins with a description of the basic structure and function of the vision system of the picking robot and em-phasizes the importance of achieving high-efficiency and high-accuracy recognition in the natural agricultural ***-sequently,various image processing techniques and vision algorithms,including color image analysis,three-dimensional depth percep-tion,and automatic object recognition technology that integrates machine learning and deep learning algorithms,were *** the same time,the paper also highlights the challenges of existing technologies in dynamic lighting,occlusion problems,fruit maturity di-versity,and real-time processing *** paper further discusses multisensor information fusion technology and discusses methods for combining visual recognition with a robotcontrol system to improve the accuracy and working rate of *** the same time,this paper also introduces innovative research,such as the application of convolutional neural networks(CNNs)for accurate fruit detection and the development of event-based vision systems to improve the response speed of the *** the end of this paper,the future development of visual recognition technology for picking robots is predicted,and new research trends are proposed,including the refinement of algorithms,hardware innovation,and the adaptability of technology to different agricultural *** purpose of this paper is to provide a comprehensive analysis of visual recognition technology for researchers and practitioners in the field of agricul-tural rob
In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and ...
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In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and then the control input is divided into an expected input and an error compensator. Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis. Subsequently,by modifying the adaptive laws and local control laws, a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system. Through the direct Lyapunov theory, the proposed scheme allows the state errors to asymptotically converge to a specified interval. Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.
This paper proposes a vision-based formation control method for multi-robot systems in the absence of inter-robot communication, employing a leader-follower scheme with a single Kinect camera as the sole sensor. By ut...
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Dear editor,This letter presents an automatic data augmentation algorithm for medical image *** increase the scale and diversity of medical images,we propose a differentiable automatic data augmentation algorithm base...
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Dear editor,This letter presents an automatic data augmentation algorithm for medical image *** increase the scale and diversity of medical images,we propose a differentiable automatic data augmentation algorithm based on proximal update by finding an optimal augmentation ***,on the one hand,a dedicated search space is designed for the medical image segmentation *** the other hand,we introduce a proximal differentiable gradient descent strategy to update the data augmentation policy,which would increase the searching *** of the experiments indicate that the proposed algorithm significantly outperforms state-of-the-art methods,and search speed is 10 times faster than state-of-the-art methods.
This paper presents a data-driven predictive control method for optimizing the energy consumption of air-cooled data centers with unknown system model parameters. First, based on the measurable data of the studied sys...
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Light field cameras are capable of capturing intricate angular and spatial details. This allows for acquiring complex light patterns and details from multiple angles, significantly enhancing the precision of image sem...
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Vision sensors are widely applied in vehicles, robots, and roadside infrastructure. However, due to limitations in hardware cost and system size, camera Field-of-View (FoV) is often restricted and may not provide suff...
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Vision sensors are widely applied in vehicles, robots, and roadside infrastructure. However, due to limitations in hardware cost and system size, camera Field-of-View (FoV) is often restricted and may not provide sufficient coverage. Nevertheless, from a spatiotemporal perspective, it is possible to obtain information beyond the camera's physical FoV from past video streams. In this paper, we propose the concept of online video inpainting for autonomous vehicles to expand the field of view, thereby enhancing scene visibility, perception, and system safety. To achieve this, we introduce the FlowLens architecture, which explicitly employs optical flow and implicitly incorporates a novel clip-recurrent transformer for feature propagation. FlowLens offers two key features: 1) FlowLens includes a newly designed Clip-Recurrent Hub with 3D-Decoupled Cross Attention (DDCA) to progressively process global information accumulated over time. 2) It integrates a multi-branch Mix Fusion Feed Forward Network (MixF3N) to enhance the precise spatial flow of local features. To facilitate training and evaluation, we derive the KITTI360 dataset with various FoV mask, which covers both outer- and inner FoV expansion scenarios. We also conduct quantitative assessments of beyond-FoV semantics across different models and perform qualitative comparisons of beyond-FoV object detection. We illustrate that employing FlowLens to reconstruct unseen scenes even enhances perception within the field of view by providing reliable semantic context. Extensive experiments and user studies involving offline and online video inpainting, as well as beyond-FoV perception tasks, demonstrate that FlowLens achieves state-of-the-art performance. The source code and dataset are made publicly available at https://***/MasterHow/FlowLens. IEEE
This paper investigates a dexterous manipulation method for multi-fingered hands based on the approximate policy optimization (PPO) algorithm. First, a prior knowledge base of dexterous manipulation demonstration data...
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Aiming at the current problem of lack of effective data and high service latency for intrusion detection in smart substations, this paper proposes a lightweight intrusion detection method for smart substations. Throug...
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This paper deals with the problem of combining task and motion planning for a manipulator system. We propose a linear temporal logic (LTL) approach which follows the traditional hierarchical planning process, includin...
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