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Aiming at the weak stiffness of the series support mechanism of the partial-face boring machine, poor adaptability of the non-circular TBM section, and difficulties in dealing with the blind area of excavation, a partial-face TBM propulsion mechanism based on the 6-SPS parallel mechanism is designed, and a stiffness prediction model establishment method considering the local flexibility of the platform is proposed. Firstly, the geological conditions is selected, the propulsion reaction force is calculated according to the total thrust prediction model, and the propulsion mechanism is designed. On the basis of inverse kinematics; the rectangular coordinate boundary search method is used to calculate the position workspace of the mechanism. Then, by deriving the micro-displacement mapping between branch chain and the platform, the branch chain is considered, the gravity of the moving platform is regarded as an external load, and the finite element software is used to identify the flexibility coefficient at the contact point between the platform and the branch chain; a semi-analytical static stiffness model of the propulsion mechanism is established, which is verified by the finite element software. Finally, the influence of the local flexibility of the platform on the stiffness performance is compared and analyzed, and the results show that the stiffness model considering the local flexibility of the platform is more accurate. This study provides a theoretical basis for the design and development of the partial-face TBM propulsion mechanism.

To eliminate blind spots in the field of vision and achieve a safe and collision‐free path, this paper proposes a path planning method based on multivehicle collaborative mapping in the context of vehicle networking. First, a multi vehicle map merging strategy based on the fireworks algorithm is proposed. In this strategy, a dissimilarity objective function based on the concept of grid map similarity is established and an improved fireworks algorithm is used to quickly search for the maximum overlap between local maps, achieving multivehicle collaborative mapping. Second, a real‐time path planning method based on artificial potential field theory is proposed. The information obtained from multivehicle collaborative mapping is first combined with the potential field model to form a multifield coupled road environment model. Then, the obstacle repulsion potential field model is improved to address the issues of traditional artificial potential field methods that target unreachability and poor dynamic response. The feasibility and effectiveness of the collaborative path planning method and single vehicle path planning method are tested through simulation analysis. This paper demonstrates through simulation analysis that the proposed path planning method can effectively achieve beyond line of sight perception and safely and comfortably guide vehicles to complete path planning. [ABSTRACT FROM AUTHOR]

Taking China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) journal database as data sources, the annual publication volume of the research literature, author-institution cooperation distribution, research hotspots, and evolution trends from the domestic and foreign research literature on module division from 2000 to 2019 were visually analyzed with the CiteSpace software to draw scientific knowledge graph. It was pointed out that the research in the field of module division was paid close attention by seniors at home and abroad, and it experienced the following three stages: the initial exploration period (2000-2008), the rapid growth period (2009-2015), and the steady development period (2016-2019). From the perspective of the distribution of core authors and research institutions, it was found that China and the United States had the most outstanding research results in the field of module division. It indicated that China had become the backbone of this field in the international stage and the developed countries such as the United States were still the main research groups. The domestic and foreign research focused on the product's green module division, product design, mass customization, etc. However, foreign researches focused on the multi-disciplinary field, such as complex network, multi-objective optimization and biological network modularity. The domestic researches focused on theoretical methods of the module division with a narrow application scope. The future research will be conducted on key words such as national gene network, dynamic analysis, digital twin, etc. Among them, solving the organization and layout of the complex product's life cycle modules as well as applying digital twins to grasp the granularity of product function modules will be the focus and direction for the future research. [ABSTRACT FROM AUTHOR]

Aiming at the multi-dimensional and strong coupling problem of design and manufacturing caused by the high dimensionality of systems and large number of units of complex mechanical products, a module partition method based on spectral clustering algorithm was proposed. The hierarchical decomposition of products was realized based on the function-flow-structure decomposition method, and fuzzy mathematics was used to define the correlation between feature elements. On this basis, the association relation model of product parts based on numerical design structure matrix was constructed. By introducing the spectral clustering algorithm, the component clustering problem was transformed into the optimal division problem of the graph, and the evaluation index of module division based on the average cohesion within the module and the average coupling between the modules was constructed to realize the module division of the products. The results of the examples showed that the method could effectively reduce the complexity of the design and manufacturing of complex mechanical products, and the method was scientifically effective. [ABSTRACT FROM AUTHOR]

Pedestrian detection, as a research hotspot in the field of computer vision, is widely used in many fields, such as automatic driving, video surveillance, robots and so on. In recent years, with the rapid development of deep learning, pedestrian detection technology has made unprecedented breakthroughs. However, it fails to saturate pedestrian detection research, and there are still many problems to be solved. This study reviews the current research status of pedestrian detection methods based on deep learning. In the first place, we summarised the research results of two stage and one stage pedestrian detection based on deep learning, also summarised and analysed the improvement methods. Meanwhile, we focused on the occlusion and multi‐scale problems of pedestrian detection and discussed the corresponding solutions. At last, we induced the pedestrian detection datasets and evaluation methods and prospected the development trend of deep learning in pedestrian detection. [ABSTRACT FROM AUTHOR]