Guojun Chen^*, Danguo Cheng, Wei Chen, Xue Yang, Tiezheng Guo

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3721-3741, 2024, DOI:10.32604/cmc.2024.047325

Abstract With the increase in ocean exploration activities and underwater development, the autonomous underwater vehicle (AUV) has been widely used as a type of underwater automation equipment in the detection of underwater environments. However, nowadays AUVs generally have drawbacks such as weak endurance, low intelligence, and poor detection ability. The research and implementation of path-planning methods are the premise of AUVs to achieve actual tasks. To improve the underwater operation ability of the AUV, this paper studies the typical problems of path-planning for the ant colony algorithm and the artificial potential field algorithm. In response to the limitations of a single… More >

Xinci Zhou, Jin Zhu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2705-2727, 2024, DOI:10.32604/cmes.2024.046363

Abstract As the number of automated guided vehicles (AGVs) within automated container terminals (ACT) continues to rise, conflicts have become more frequent. Addressing point and edge conflicts of AGVs, a multi-AGV conflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards. For larger terminal maps and complex environments, the grid method is employed to model AGVs’ road networks. An improved bounded conflict-based search (IBCBS) algorithm tailored to ACT is proposed, leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range. Comparative experiments involving 60… More >

Zhiwei Lin¹, Hui Wang^1,*, Tianding Chen¹, Yingtao Jiang², Jianmei Jiang³, Yingpin Chen¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1357-1379, 2024, DOI:10.32604/cmes.2023.045990

Abstract In the domain of autonomous industrial manipulators, precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance, such as handling, heat sealing, and stacking. While Multi-Degree-of-Freedom (MDOF) manipulators offer kinematic redundancy, aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites, their path planning entails intricate multi-objective optimization, encompassing path, posture, and joint motion optimization. Achieving satisfactory results in practical scenarios remains challenging. In response, this study introduces a novel Reverse Path Planning (RPP) methodology tailored for industrial manipulators. The approach commences by conceptualizing the manipulator’s end-effector as an… More > Graphic Abstract

Xiaoge Wei^1,2,*, Yuming Zhang^1,2, Huaitao Song^1,2, Hengjie Qin^1,2, Guanjun Zhao³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1295-1316, 2024, DOI:10.32604/cmes.2023.045096

Abstract Reducing casualties and property losses through effective evacuation route planning has been a key focus for researchers in recent years. As part of this effort, an enhanced sparrow search algorithm (MSSA) was proposed. Firstly, the Golden Sine algorithm and a nonlinear weight factor optimization strategy were added in the discoverer position update stage of the SSA algorithm. Secondly, the Cauchy-Gaussian perturbation was applied to the optimal position of the SSA algorithm to improve its ability to jump out of local optima. Finally, the local search mechanism based on the mountain climbing method was incorporated into the local search stage of… More >

Yuting Liu¹, Hongwei Ding^1,*, Zongshan Wang^1,*, Gaurav Dhiman^2,3,4, Zhijun Yang¹, Peng Hu⁵

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2385-2406, 2023, DOI:10.32604/cmc.2023.039883

Abstract The equilibrium optimizer (EO) represents a new, physics-inspired metaheuristic optimization approach that draws inspiration from the principles governing the control of volume-based mixing to achieve dynamic mass equilibrium. Despite its innovative foundation, the EO exhibits certain limitations, including imbalances between exploration and exploitation, the tendency to local optima, and the susceptibility to loss of population diversity. To alleviate these drawbacks, this paper introduces an improved EO that adopts three strategies: adaptive inertia weight, Cauchy mutation, and adaptive sine cosine mechanism, called SCEO. Firstly, a new update formula is conceived by incorporating an adaptive inertia weight to reach an appropriate balance… More >

Tianfeng Xu¹, Tao Wang¹, Chengming Ye², Jing Zhang¹, Peng Xi¹, Yunhui Chen², Gengwu Zhang^3,*

Energy Engineering, Vol.120, No.11, pp. 2629-2650, 2023, DOI:10.32604/ee.2023.027537

Abstract In order to improve the reliability of power supply, the sophisticated design of the structure of electric cable network has become an important issue for modern urban distribution networks. In this paper, an electric cable path planning model based on heuristic optimization algorithm considering mixed-land scenario is proposed. Firstly, based on different land samples, the kernel density estimation (KDE) and the analytic hierarchy process (AHP) are used to estimate the construction cost of each unit grid, in order to construct the objective function of comprehensive investment for electric cable loop network. Then, the ant colony optimization (ACO) was improved in… More >

Xiaoli Li, Tongtong Jiao^#, Jinfeng Ma, Dongxing Duan, Shengbin Liang^#,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 595-617, 2024, DOI:10.32604/cmes.2023.029367

Abstract In view of the complex marine environment of navigation, especially in the case of multiple static and dynamic obstacles, the traditional obstacle avoidance algorithms applied to unmanned surface vehicles (USV) are prone to fall into the trap of local optimization. Therefore, this paper proposes an improved artificial potential field (APF) algorithm, which uses 5G communication technology to communicate between the USV and the control center. The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios. Considering the various scenarios between the USV and other dynamic obstacles… More > Graphic Abstract

Trong-The Nguyen^1,2,3, Thi-Kien Dao^1,2,3,*, Trinh-Dong Nguyen^2,3

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3213-3234, 2023, DOI:10.32604/iasc.2023.041356

Abstract Wireless sensor networks (WSNs) are widely used for various practical applications due to their simplicity and versatility. The quality of service in WSNs is greatly influenced by the coverage, which directly affects the monitoring capacity of the target region. However, low WSN coverage and uneven distribution of nodes in random deployments pose significant challenges. This study proposes an optimal node planning strategy for network coverage based on an adjusted single candidate optimizer (ASCO) to address these issues. The single candidate optimizer (SCO) is a metaheuristic algorithm with stable implementation procedures. However, it has limitations in avoiding local optimum traps in… More >

Loc Q. Huynh¹, Ly V. Tran¹, Phuc N. K. Phan¹, Zhiqiu Yu², Son V. T. Dao^1,2,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2281-2300, 2023, DOI:10.32604/cmc.2023.034872

Abstract Path planning is a prevalent process that helps mobile robots find the most efficient pathway from the starting position to the goal position to avoid collisions with obstacles. In this paper, we propose a novel path planning algorithm–Intermediary RRT*-PSO-by utilizing the exploring speed advantages of Rapidly exploring Random Trees and using its solution to feed to a metaheuristic-based optimizer, Particle swarm optimization (PSO), for fine-tuning and enhancement. In Phase 1, the start and goal trees are initialized at the starting and goal positions, respectively, and the intermediary tree is initialized at a random unexplored region of the search space. The… More >

Chong Xu¹, Hao Zhu¹, Haotian Zhu², Jirong Wang¹, Qinghai Zhao^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2567-2591, 2023, DOI:10.32604/cmes.2023.029152

Abstract A new and improved RRT^∗ algorithm has been developed to address the low efficiency of obstacle avoidance planning and long path distances in the electric vehicle automatic charging robot arm. This algorithm enables the robot to avoid obstacles, find the optimal path, and complete automatic charging docking. It maintains the global completeness and path optimality of the RRT algorithm while also improving the iteration speed and quality of generated paths in both 2D and 3D path planning. After finding the optimal path, the B-sample curve is used to optimize the rough path to create a smoother and more optimal path.… More > Graphic Abstract