In this paper, we consider the problem of verifying pre-opacity for discrete-time control systems. Preopacity is an important information-flow security property that secures the intention of a system to execute some s...
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Today’s Internet is experiencing a massive number of users with a continuously increasing need for data, which is the leading cause of introduced limitations among security and privacy issues. To overcome these limit...
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Platoon control of autonomous industrial vehicles contributes to improving the safety and reliability of cargo transportation in complex industrial scenarios, increasing traffic efficiency and saving energy. The plato...
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Non-rigid point set registration is an essential technique in fields such as robotics, computer vision, image-guided surgery, and augmented reality. However, effectively addressing non-rigid deformations and handling ...
Non-rigid point set registration is an essential technique in fields such as robotics, computer vision, image-guided surgery, and augmented reality. However, effectively addressing non-rigid deformations and handling noise interference remains a significant challenge in this context. This paper introduces a novel hybrid mixture model (HMM), combining a Gaussian mixture model (GMM) to describe positional features and a Fisher mixture model (FMM) to represent orientation features. This hybrid mixture model offers a solution to the non-rigid point set registration (PSR) problem. The proposed approach iteratively optimizes model parameters through the maximum expectation (EM) algorithm. It comprehensively explores registration performance, accounting for non-rigid deformations amidst isotropic and anisotropic positional noise. The proposed approach further incorporates reliable normal vectors for evaluating orientation features. Extensive experiments on non-rigid PSR demonstrates the improvements our algorithm offers in terms of both robustness and accuracy.
Formation tracking (FT) control aims at handling cooperative tasks in multi-agent systems (MASs) to achieve desired performance. In these tasks, the leader’s input is generally non-zero and unknown to all followers, ...
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Lithium-ion batteries are widely applied in sustainable energy conversion system. Consequently, it is of great research significance to accurately estimate the state of health (SOH) of batteries. To effectively model ...
Lithium-ion batteries are widely applied in sustainable energy conversion system. Consequently, it is of great research significance to accurately estimate the state of health (SOH) of batteries. To effectively model the input features at the spatial level, this article proposes a self-attention graph pooling convolutional network (SAGPCN) to estimate the SOH. The advantages of SAGPCN proposed in this paper can be reflected as follows: (1) The SAGPCN can consider node characteristics and graph topology, which focuses the attention on key parts of the graph. (2) The SAGPCN designs a self-attention mechanism to reserve significant nodes and delete secondary nodes, so as to optimize the network structure. A real-world dataset is adopted to evaluate the proposed battery SOH estimation approach in this paper. Experimental results represent that the estimation performance of the proposed SAGPCN is better than some data-driven SOH prediction approaches.
Continuous-time (CT) modeling has proven to provide improved sample efficiency and interpretability in learning the dynamical behavior of physical systems compared to discrete-time (DT) models. However, even with nume...
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Reinforcement learning methods as a promising technique have achieved superior results in the motion planning of free-floating space robots. However, due to the increase in planning dimension and the intensification o...
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Active speaker detection (ASD) systems are important modules for analyzing multi-talker conversations. They aim to detect which speakers or none are talking in a visual scene at any given time. Existing research on AS...
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This paper focuses on the localization of a McNamee wheel mobile robot, which has six states of motion and more complex kinematic equations than a normal mobile robot using a McNamee wheel. In this paper, the kinemati...
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