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  • Open Access

    ARTICLE

    A Hybrid Path Planning Method Based on Articulated Vehicle Model

    Zhongping Chen1, Dong Wang1, *, Gang Chen2, Yanxi Ren3, Danjie Du4

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1781-1793, 2020, DOI:10.32604/cmc.2020.010902

    Abstract Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature… More >

  • Open Access

    ARTICLE

    Intelligent Service Robot Vision Control Using Embedded System

    Li-Hong Juang1, Shengxiang Zhang2

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 451-458, 2019, DOI:10.31209/2019.100000126

    Abstract Intelligent robots are the combination of computer engineering, software engineering, control engineering, electronic engineering, mechanical engineering, and systems design engineering in order to design, and manufacture useful products. In this paper, the author derives some novel computing and algorithm applications on computer vision and image processing and intelligent control and navigation of mobile robots for the intelligent service robot system. In this paper, we proposed an idea of flexible design for a intelligent service robot, which refers to a single robot with a variety of flexure structure. We presented an integrated system for vision-guided finding the person and completing obstacle… More >

  • Open Access

    ARTICLE

    Applying Probabilistic Model Checking to Path Planning in an Intelligent Transportation System Using Mobility Trajectories and Their Statistical Data

    Honghao Gao1, 2, 5, Wanqiu Huang1, 4, Xiaoxian Yang3

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 547-559, 2019, DOI:10.31209/2019.100000110

    Abstract Path planning is an important topic of research in modern intelligent traffic systems (ITSs). Traditional path planning methods aim to identify the shortest path and recommend this path to the user. However, the shortest path is not always optimal, especially in emergency rescue scenarios. Thus, complex and changeable factors, such as traffic congestion, road construction and traffic accidents, should be considered when planning paths. To address this consideration, the maximum passing probability of a road is considered the optimal condition for path recommendation. In this paper, the traffic network is abstracted as a directed graph. Probabilistic data on traffic flow… More >

  • Open Access

    ARTICLE

    Simulation of Real‐Time Path Planning for Large‐Scale Transportation Network Using Parallel Computation

    Jiping Liua,b, Xiaochen Kanga,*, Chun Donga, Fuhao Zhanga

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 65-77, 2019, DOI:10.31209/2018.100000013

    Abstract To guarantee both the efficiency and accuracy of the transportation system, the real-time status should be analyzed to provide a reasonable plan for the near future. This paper proposes a model for simulating the real-world transportation networks by representing the irregular road networks with static and dynamic attributes, and the vehicles as moving agents constrained by the road networks. The all pairs shortest paths (APSP) for the networks are calculated in a real-time manner, and the ever-changing paths can be used for navigating the moving vehicles with real-time positioning devices. In addition, parallel computation is used to accelerate the shortest… More >

  • Open Access

    ARTICLE

    A Novel Improved Bat Algorithm in UAV Path Planning

    Na Lin1, Jiacheng Tang1, Xianwei Li2,3, Liang Zhao1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 323-344, 2019, DOI:10.32604/cmc.2019.05674

    Abstract Path planning algorithm is the key point to UAV path planning scenario. Many traditional path planning methods still suffer from low convergence rate and insufficient robustness. In this paper, three main methods are contributed to solving these problems. First, the improved artificial potential field (APF) method is adopted to accelerate the convergence process of the bat’s position update. Second, the optimal success rate strategy is proposed to improve the adaptive inertia weight of bat algorithm. Third chaos strategy is proposed to avoid falling into a local optimum. Compared with standard APF and chaos strategy in UAV path planning scenarios, the… More >

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