Roadside camera-driven 3D object detection is a crucial task in intelligent transportation systems, which extends the perception range beyond the limitations of vision-centric vehicles and enhances road safety. While ...
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In this work, we focus on improving the robot's dexterous capability by exploiting visual sensing and adaptive force control. TeachNet, a vision-based teleoperation learning framework, is exploited to map human ha...
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This paper focuses on the formation tracking problem of aerial robot swarms without linear velocity measurements over directed interaction topologies. A distributed formation controller is designed for a quadrotor swa...
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ISBN:
(纸本)9781665405362
This paper focuses on the formation tracking problem of aerial robot swarms without linear velocity measurements over directed interaction topologies. A distributed formation controller is designed for a quadrotor swarm under a directed graph using the hierarchical control structure. First, the outer-loop controller governs the translational motion to achieve the desired formation, where the filter-like auxiliary dynamic system is designed for each quadrotor to overcome the lack of the linear velocity measurements. Next, based on the geometric attitude representing, an almost-global inner-loop controller is proposed to regulate the attitude of each quadrotor, which is not only coordinate-free but also the strongest possible controller in terms of the region of convergence. Furthermore, necessary and sufficient conditions for the formation tracking problem over the directed graph are presented so that the stability analysis is guaranteed. Finally, simulation results are provided to show the effectiveness of the proposed control algorithms.
Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, hav...
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The distribution network is developing towards the direction of Internet of Things in Electricity(IoTE). As an emerging technology of the Internet of Things(IoT), edge computing has great application potential in the ...
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This article presents a novel iterative deep homography network based on correlation content calculation (IDHN-CCC) for high-precision image registration of a fly-capture imaging system. The new high-precision fly-cap...
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This article presents a novel iterative deep homography network based on correlation content calculation (IDHN-CCC) for high-precision image registration of a fly-capture imaging system. The new high-precision fly-capture imaging (HFI) system is designed to obtain high-resolution images of radar microwave components (RMCs) and improve surface defect detection efficiency and autonomy while reducing hardware costs. The HFI consists of four subsystems: image acquisition mechanism, control system, image registration algorithm, and software system, which could achieve clear capture and precise imaging of RMC at high speed. The system adopts the IDHN-CCC algorithm to reduce the impact of motion errors on imaging stitching quality, which does not rely on precise camera motion positioning and coordinate transformation to achieve high-precision registration of multiple continuous shooting images. The experimental studies demonstrated the advantages of the IDHN-CCC-based HFI, which can achieve RMC images in low overlap rate fly-capture scenes with high registration accuracy.
Hand synergy from neuroscience provides an effective tool for anthropomorphic hands to realize versatile grasping with simple planning and control. This paper aims to extend the synergy-inspired design from anthropomo...
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ISBN:
(数字)9781728173955
ISBN:
(纸本)9781728173962
Hand synergy from neuroscience provides an effective tool for anthropomorphic hands to realize versatile grasping with simple planning and control. This paper aims to extend the synergy-inspired design from anthropomorphic hands to multi-fingered robot hands. The synergy-inspired hands are not necessarily humanoid in morphology but perform primary characteristics and functions similar to the human hand. At first, the biomechanics of hand synergy is investigated. Three biomechanical characteristics of the human hand synergy are explored as a basis for the mechanical simplification of the robot hands. Secondly, according to the synergy characteristics, a three-fingered hand is designed, and its kinematic model is developed for the analysis of some typical grasping and manipulation functions. Finally, a prototype is developed and preliminary grasping experiments validate the effectiveness of the design and analysis.
To further understand the underlying mechanism of various reinforcement learning (RL) algorithms and also to better use the optimization theory to make further progress in RL, many researchers begin to revisit the lin...
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Leveraging line features to improve localization accuracy of point-based visual-inertial SLAM (VINS) is gaining interest as they provide additional constraints on scene structure. However, real-time performance when i...
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In urban construction, transportation system is an important part. However, the pavement cracks will occur because of using in long time and some external force collision, which has impacts on the safety and reliabili...
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ISBN:
(纸本)9781665426480
In urban construction, transportation system is an important part. However, the pavement cracks will occur because of using in long time and some external force collision, which has impacts on the safety and reliability of the whole transportation system. Therefore, it is necessary to detect the pavement cracks. The formation of pavement cracks is slow, and it is not concentrated on one place, so it is difficult to obtain enough images containing cracks to train. We propose a new pre-training method based on self-supervision study, which can obtain features closer to the target task from normal pavement images. In addition, we combine a memory-augment convolutional autoencoder and a hard-threshold module to improve the accuracy of the crack classification. Experiments conducted on the Mendeley Concrete crack dataset and Deep-Crack dataset demonstrate the good performance in pavement crack classification task.
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