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With the development of mobile edge computing and neural network Deep Learning (DL), more and more scholars are studying the combination of the two. This paper mainly studies the application of mobile edge computing and neural network DL in IoT computing collaboration and data-aware routing algorithms. Therefore, this paper proposes the deployment options of MEC technology and ETSIMEC in mobile edge computing, combining mobile edge computing with DL, designs an optimization algorithm based on Markov decision process and feature expression learning, and then analyzes and optimizes IoT computing and VANET routing algorithm. In order to have a clearer direction for the optimization algorithm, this paper also designs the edge computing model training and experiment comparison, the DL algorithm comparison experiment, and the routing algorithm simulation experiment and performance analysis. Combined with the experimental results, it is optimized and compared with traditional IoT computing and routing algorithms. Finally, it is concluded that the computing efficiency of IoT computing based on edge computing and DL designed in this paper is 21.33% higher than that of traditional IoT computing. The efficiency of the routing algorithm based on edge computing and DL designed in this paper is 9.29% higher than that of the traditional routing algorithm. [ABSTRACT FROM AUTHOR]

A novel visual servoing method is proposed to synchronously capture a malfunctional satellite's docking ring by two space manipulators. Due to the lack of conspicuous visual marks, structured light is implemented to estimate the ring's pose. To ensure the capturing process's security, two aspects are investigated. Spatially, capturing target points for two manipulators are planned together by considering the chaser's orientation. As a consequence, collision risk between two manipulators is eliminated. Temporally, by adding duration parameters in trajectory generation algorithm, capturing synchronism for two manipulators is guaranteed. Experimental results show that, by the proposed method, a tumbling target was successfully captured by two space manipulators. Compared to existing methods, the collision risk between two manipulators is thoroughly eliminated and the capturing synchronism is improved remarkably. [ABSTRACT FROM AUTHOR]