In this paper, according to the different dynamic models of the support phase and the swing phase, the joint torque compensation of the support phase and the swing phase are given to compensate the joint torque of the...
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ISBN:
(纸本)9781665478977
In this paper, according to the different dynamic models of the support phase and the swing phase, the joint torque compensation of the support phase and the swing phase are given to compensate the joint torque of the hydraulic quadruped robot controlled by the virtual model control(VMC). This compensation can increase the tracking effect of the foot end on the swing trajectory, reduce the elasticity and damping coefficient of the virtual model method, and increase the flexibility of the leg. Then this paper establishes the touchdown detection function based on the joint torque obtained by the Lagrange dynamics equation and the joint torque obtained by the force sensor to determine the touch state of the foot of the quadruped robot to switch the phase of the leg. At the end of this paper, simulation and experiment prove that the compensation model and touchdown detection function model have feasibility and correctness.
Targets grouping is the basis of second-level information fusion,which can effectively assist commanders to make *** aerial targets grouping algorithm only takes the radar acquisition data at the current time as the o...
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Targets grouping is the basis of second-level information fusion,which can effectively assist commanders to make *** aerial targets grouping algorithm only takes the radar acquisition data at the current time as the object and cannot update the clustering results automatically.A grouping method combining dynamic time warping(DTW) and the algorithm Density-Based Spatial Clustering of Applications with Noise(DBSCAN) is *** DTW distance of each attribute historical time-series data is used to measure the similarity between ***,an improved DBSCAN algorithm is used for *** simulation results show that the method has better grouping effect and can automatically cluster regularly.
This paper studies the problem of stabilizing a self-triggered controlsystem with quantized output. Employing a standard observer-based state feedback control law, a self-triggering mechanism that dictates the next s...
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Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively lear...
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Zero-shot object detection aims to localize and recognize objects of unseen classes. Most of existing works face two problems: the low recall of RPN in unseen classes and the confusion of unseen classes with backgroun...
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Zero-shot object detection aims to localize and recognize objects of unseen classes. Most of existing works face two problems: the low recall of RPN in unseen classes and the confusion of unseen classes with backgroun...
Zero-shot object detection aims to localize and recognize objects of unseen classes. Most of existing works face two problems: the low recall of RPN in unseen classes and the confusion of unseen classes with background. In this paper, we present the first method that combines DETR and meta-learning to perform zero-shot object detection, named Meta-ZSDETR, where model training is formalized as an individual episode based meta-learning task. Different from Faster R-CNN based methods that firstly generate class-agnostic proposals, and then classify them with visual-semantic alignment module, Meta-ZSDETR directly predict class-specific boxes with class-specific queries and further filter them with the predicted accuracy from classification head. The model is optimized with meta-contrastive learning, which contains a regression head to generate the coordinates of class-specific boxes, a classification head to predict the accuracy of generated boxes, and a contrastive head that utilizes the proposed contrastive-reconstruction loss to further separate different classes in visual space. We conduct extensive experiments on two benchmark datasets MS COCO and PASCAL VOC. Experimental results show that our method outperforms the existing ZSD methods by a large margin.
In recent years, micromanipulation technology has achieved extensive applications in industry and life science. Improving the precision and bandwidth of the micromanipulator and simultaneously reducing size, weight, a...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
In recent years, micromanipulation technology has achieved extensive applications in industry and life science. Improving the precision and bandwidth of the micromanipulator and simultaneously reducing size, weight, and cost pose significant challenges to the existing micromanipulator design and fabrication methods. Here, we propose a 3-RRS micromanipulator with an origami-inspired spherical joint based on the PC-MEMS process, aiming for miniaturization and cost-effectiveness. The spherical joint allows rotations of 140° around the x-axis approximately, 140° around the y-axis approximately, and 20° around the z-axis approximately. The micromanipulator has weights of 0.8 g, dimensions of 16 mm × 16 mm × 22 mm, and workspace of 0.7 mm
3
. The end platform of the micromanipulator can be equipped with various effectors to accomplish different kinds of tasks. Experimental results validated its high precision and bandwidth, exhibiting its potential to perform intricate micromanipulation tasks.
The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by prese...
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In this paper, an effective joint beam selection and power allocation（JBSPA） method is proposed to solve the online resource scheduling problem for multi-target tracking in distributed MIMO radar system. Overall tar...
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In this paper, an effective joint beam selection and power allocation（JBSPA） method is proposed to solve the online resource scheduling problem for multi-target tracking in distributed MIMO radar system. Overall target tracking performance can be improved by optimizing radar system beam selection and power allocation, since each MIMO radar can generate a timevarying beam, and adjust the quality of the observed signal by controlling the transmit power of each beam. In our method the feedback information of the target tracking period is used to complete the optimal radar-targets assignment and power allocation,the objective function is formulated based on the Bayesian Cramér-Rao lower bound, as the formulated JBSPA problem is nonconvex, a three steps solution method based on reward matrix is proposed to solve it effectively. Numerical results show that the proposed JBSPA method can deliver better performance than the competitors in overall MTT performance.
This paper discusses the complete area coverage of multi-robots in unknown environments. Finding the optimal solution for the problem of area coverage with multiple robots has been proven to be NP-hard. This paper pro...
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This paper discusses the complete area coverage of multi-robots in unknown environments. Finding the optimal solution for the problem of area coverage with multiple robots has been proven to be NP-hard. This paper proposes the Multiagent Node Backtracking Area Coverage（MANBAC） algorithm, which uses improved BCD local area coverage method, and the node backtracking method that is based on the A* algorithm to achieve complete coverage of the entire unknown *** with the area coverage of a single robot, use multi robots can greatly improve the efficiency of area *** with the existing coverage algorithms in known area, this study can be applied to a wider range of area scenarios which are not known.
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