Due to the limited visual field of UGV, it is difficult to detect the accessible zone in a wide range of area in real time. This paper proposes a UAV-aided autonomous road network construction method where roads are p...
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In this paper, an approximate constrained optimal guidance law is proposed for Mars entry vehicles guidance. Firstly, the original guidance of Mars entry vehicle is transformed into a fixed-time optimal tracking contr...
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ISBN:
(纸本)9781467374439
In this paper, an approximate constrained optimal guidance law is proposed for Mars entry vehicles guidance. Firstly, the original guidance of Mars entry vehicle is transformed into a fixed-time optimal tracking control problem, which depends on the solution of the Hamilton-Jacobi-Bellman(HJB) equation. Considering the case the control input is constrained, a generalized non-quadratic performance index is defined. In general, the HJB equation is a nonlinear partial differential equation that is difficult or even impossible to be solved analytically. To overcome the difficulty, neural network(NN) is used to solve the HJB equation approximately. Subsequently, the Monte-Carlo integration method and Latin Hypercube Sampling(LHS) are introduced to compute the integrals on multi-dimensional domains. Finally, the Monte-Carlo simulation results on the Mars entry vehicle demonstrate the effectiveness of the proposed method.
An estimate-and-forward(EF) scheme for single-input single-output(SISO) and multiple-input multiple-output(MIMO) full-duplex two-way relay networks is proposed and analyzed. The relay estimates the received signal fro...
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An estimate-and-forward(EF) scheme for single-input single-output(SISO) and multiple-input multiple-output(MIMO) full-duplex two-way relay networks is proposed and analyzed. The relay estimates the received signal from two terminal nodes by a minimum mean squared error(MMSE) estimation and forwards a scaled version of the MMSE estimate to the destination. The proposed EF outperforms conventional amplify-and-forward(AF) and decode-and-forward(DF) across all signal-to-noise ratio(SNR) region. Because its computational complexity is high for relays with a large number of antennas(large MIMO) and/or high order constellations, an approximate EF scheme, called list EF, are thus proposed to reduce the computational complexity. The proposed list EF computes a candidate list for the MMSE estimate by using a sphere decoder, and it approaches the performance of the exact EF relay at a negligible performance loss. The proposed forwarding approach also could be used to other relay networks, such as half-duplex, one-way or massive MIMO relay networks.
Dear editor,Deep reinforcement learning(DRL),combining the perception capability of deep learning(DL)and the decision-making capability of reinforcement learning(RL)[1],has been widely investigated for autonomous driv...
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Dear editor,Deep reinforcement learning(DRL),combining the perception capability of deep learning(DL)and the decision-making capability of reinforcement learning(RL)[1],has been widely investigated for autonomous driving decision-making *** this letter,Fund:supported in part by the National Natural Science Foundation of China(NSFC)(62173325);the Beijing Municipal Natural Science Foundation(L191002).
Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on ...
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Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on deep neural networks are able to achieve impressive results.
Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simpl...
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Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simplified expression of light fields with depth information discarded. In theory, computer vision tasks may achieve better performance as long as complete light fields are acquired.
For a high precision Non-Uniform Rational B-Spline(NURBS) interpolator, calculating the parameter of the next path interpolating point is an indispensable step, which affects feedrate fluctuation. This paper presents ...
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ISBN:
(纸本)9781467374439
For a high precision Non-Uniform Rational B-Spline(NURBS) interpolator, calculating the parameter of the next path interpolating point is an indispensable step, which affects feedrate fluctuation. This paper presents a new, simple and precise interpolation algorithm for parameter curve which adopts first-order Taylor's expansion, and then make use of the bisection method to achieve accurate path parameters. In the meanwhile, the interpolator is restricted from geometric and kinematical constraints. A simulation study is conducted to demonstrate the advantages of proposed interpolation algorithm compared with other algorithms for the parametric curves represented in the NURBS form.
This paper concerns a novel optimal self-learning battery sequential control scheme for smart home energy systems. The main idea is to use the adaptive dynamic programming U+0028 ADP U+0029 technique to obtain the opt...
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Interactive image segmentation which needs the user to give certain hard constraints has shown promising performance for object segmentation. In this paper, we consider characters in text image as a special kind of ob...
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This paper focuses on a class of unknown discrete-time nonlinear systems with dead-zone control constraints based on adaptive dynamic programming (ADP). The discrete-time Hamilton-Jacobi-Bellman (DTHJB) equation corre...
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