This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the co...
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This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the control objective. The DF mapping refers to the fact that the system state and input of each robot can be derived algebraically from the flat outputs of the leaders and the cooperative errors and their finite order derivatives. Based on the proposed swarm DF mapping, a distributed controller is designed. The distributed implementation of swarm DF mapping is achieved through observer design. The effectiveness of the proposed method is validated through a numerical simulation of quadrotor swarm synchronization.
With the rapid development of semiconductor in- dustry, the number of cores integrated on chip increases quickly, which brings tough challenges such as bandwidth, scalability and power into on-chip interconnection. Un...
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With the rapid development of semiconductor in- dustry, the number of cores integrated on chip increases quickly, which brings tough challenges such as bandwidth, scalability and power into on-chip interconnection. Under such background, Network-on-Chip (NoC) is proposed and gradually replacing the traditional on-chip interconnections such as sharing bus and crossbar. For the convenience of physical layout, mesh is the most used topology in NoC design. Routing algorithm, which decides the paths of pack- ets, has significant impact on the latency and throughput of network. Thus routing algorithm plays a vital role in a wellperformed network. This study mainly :focuses on the routing algorithms of mesh NoC. By whether taking network information into consideration in routing decision, routing algorithms of NoC can be roughly classified into oblivious routing and adaptive routing. Oblivious routing costs less without adaptiveness while adaptive routing is on the contrary. To combine the advantages of oblivious and adaptive routing algorithm, half-adaptive algorithms were proposed. In this paper, the concepts, taxonomy and features of routing algorithms of NoC are introduced. Then the importance of routing algorithms in mesh NoC is highlighted, and representative routing algorithms with respective features are reviewed and summarized. Finally, we try to shed light upon the future work of NoC routing algorithms.
Grasp detection is a visual recognition task where the robot makes use of its sensors to detect graspable objects in its *** the steady progress in robotic grasping,it is still difficult to achieve both real-time and ...
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Grasp detection is a visual recognition task where the robot makes use of its sensors to detect graspable objects in its *** the steady progress in robotic grasping,it is still difficult to achieve both real-time and high accuracy grasping *** this paper,we propose a real-time robotic grasp detection method,which can accurately predict potential grasp for parallel-plate robotic grippers using RGB *** work employs an end-to-end convolutional neural network which consists of a feature descriptor and a grasp *** for the first time,we add an attention mechanism to the grasp detection task,which enables the network to focus on grasp regions rather than ***,we present an angular label smoothing strategy in our grasp detection method to enhance the fault tolerance of the *** quantitatively and qualitatively evaluate our grasp detection method from different aspects on the public Cornell dataset and Jacquard *** experiments demonstrate that our grasp detection method achieves superior performance to the state-of-the-art *** particular,our grasp detection method ranked first on both the Cornell dataset and the Jacquard dataset,giving rise to the accuracy of 98.9%and 95.6%,respectively at realtime calculation speed.
Data-driven garment animation is a current topic of interest in the computer graphics *** approaches generally establish the mapping between a single human pose or a temporal pose sequence,and garment deformation,but ...
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Data-driven garment animation is a current topic of interest in the computer graphics *** approaches generally establish the mapping between a single human pose or a temporal pose sequence,and garment deformation,but it is difficult to quickly generate diverse clothed human *** address this problem with a method to automatically synthesize dressed human animations with temporal consistency from a specified human motion *** the heart of our method is a twostage ***,we first learn a latent space encoding the sequence-level distribution of human motions utilizing a transformer-based conditional variational autoencoder(Transformer-CVAE).Then a garment simulator synthesizes dynamic garment shapes using a transformer encoder-decoder *** the learned latent space comes from varied human motions,our method can generate a variety of styles of motions given a specific motion *** means of a novel beginning of sequence(BOS)learning strategy and a self-supervised refinement procedure,our garment simulator is capable of efficiently synthesizing garment deformation sequences corresponding to the generated human motions while maintaining temporal and spatial *** verify our ideas *** is the first generative model that directly dresses human animation.
The saturation problem in heterogeneous vehicle platoons is considered. With leader and predecessor following control architecture, actuator saturation in a vehicle causes its followers to collide due to their link wi...
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We consider the problem of reconstructing the initial states of an ensemble of linear systems from output measurements that are anonymized in the sense that the association between output measurements and systems in t...
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Grammatical Inference deals with the problem of learning structural models, such as grammars, from different sort of data patterns, such as artificial languages, natural languages, biosequences, speech and so on. This...
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Grammatical Inference deals with the problem of learning structural models, such as grammars, from different sort of data patterns, such as artificial languages, natural languages, biosequences, speech and so on. This article describes a new grammatical inference tool, Grammar-based Classifier System (GCS) dedicated to learn grammar from data. GCS is a new model of Learning Classifier Systems in which the population of classifiers has a form of a context-free grammar rule set in a Chomsky Normal Form. GCS has been proposed to address both regular language induction and the natural language grammar induction as well as learning formal grammar for DNA sequence. In all cases near-optimal solutions or better than reported in the literature were obtained.
The article introduces the Cyber4OT dataset containing network traces concerning normal and simulated attacker-hostile activity in an Industrial control System (ICS) environment. As many as 96 traces contain over 4.25...
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The article introduces the Cyber4OT dataset containing network traces concerning normal and simulated attacker-hostile activity in an Industrial control System (ICS) environment. As many as 96 traces contain over 4.25 million packets and have over 385 MB capacity. The simulated attacks have been performed on a dedicated laboratory testbed. The testbed mimics industrial plants’ Information technology (IT) and Operational technology (OT) infrastructure. The testbed deliberately uses continuous and binary control processes of fast and slow dynamics. Industrial Programmable Logic controllers (PLCs) are used to control the processes. A dedicated industrial network provides the communication between the ICS equipment, Supervisory control and Data Acquisition (SCADA) system and Human Machine Interface (HMI) panels. The communication is configured to test multiple communication protocols, including the standard industrial Modbus protocol. The entire industrial infrastructure is connected to an external office network. Since the infrastructure and its components are typical of industrial solutions, the described dataset collected using such a realistic testbed could be beneficial for a broad scope of researchers to evaluate the vulnerability of ICSs to cyber attacks using classical and artificial intelligence methods.
The path adaptive planning control of snake-like robot is influenced by uncertain disturbance of environment variables and joint mechanism components, which leads to poor stability of path planning parameter output. I...
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