Novel Path Planning Algorithm for the Mobile Robot in Power Transformer Substation by Chunxiang Mao, Jing Ma, Pengyang Qi, Dong Wang

“…In response to the issue of low search efficiency caused by the large number of expanded nodes when mobile robots use traditional A∗ algorithm for path planning in complex environments, an improved A∗ algorithm based on four-way search has been proposed. …”
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Research on Mobile Agent Path Planning Based on Deep Reinforcement Learning by Shengwei Jin, Xizheng Zhang, Ying Hu, Ruoyuan Liu, Qing Wang, Haihua He, Junyu Liao, Lijing Zeng

“…The simulation and physical implementation results reveal that LB-DDQN achieves effective collision avoidance, while demonstrating marked enhancements in critical metrics: the path’s smoothness, energy efficiency, and motion stability exhibit average improvements exceeding 50%. …”
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Smooth Optimised A*-Guided DWA for Mobile Robot Path Planning by Liling Cao, Lei Tang, Shouqi Cao, Qing Sun, Guofeng Zhou

“…In mobile robot path planning, the traditional A* algorithm suffers from high path redundancy and poor smoothness, while the Dynamic Window Approach (DWA) tends to deviate from the global optimal path and has low efficiency in avoiding dynamic obstacles when integrated with global path planning. …”
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Research on Low-carbon Development Path of Coal-fired Power Industry by Chunsheng ZHAO, Junjun YANG, Jing WANG, Liqiang DUAN

“…The coal-fired power industry will strive for more living space through low-carbon development paths, such as improving the energy efficiency of existing units, vigorously developing high-parameter generating units with high efficiency and ultra-low emission to replace small and medium-sized coal-fired units, actively promoting the application of low-carbon technologies, carrying out carbon neutralization and multi-generation, improving the flexible peak ability of coal-fired units, and strengthening the coupling development with renewable energy.…”
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Path Optimization of Welding Robot Based on Ant Colony and Genetic Algorithm by Yan Gao, Yiwan Zhang

“…For the purpose of reducing the work efficiency and time consumption of the welding robot, the ACO is used for the shortest distance and the GA is used for the shortest time fixed-point path trajectory optimization. …”
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Catalyst Technology Breakthroughs and Exploration of Fuel Cell Vehicle Commercialization Paths by Shi Peiji, Shen Rongwei, Wei Kaixin

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Research on Path Planning of Manipulator Based on the Improved RRT-Connect Algorithm by Han Shaolong, Liu Wenqi, Liu Yuanshang, Zhang Jianlin, Liu Kaihui, Zheng Xiaoyun, Li Haolun, Wang Jianchao, Wang Xiang

“…With the development of intelligent manufacturing, manipulators are being increasingly used in the tobacco industry. Path planning of manipulators is a key technology for achieving high-efficiency production. …”
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A BIT* algorithm with dilated vertices-based path stretching strategy by Xuanle Wu, Pu Li, Zhicheng Hou

“…The existing algorithms face challenges in terms of path quality and convergence speed. To enhance planning efficiency and path optimality, this paper proposes a novel algorithm: dilated vertices-based stretching BIT* (DS-BIT*) algorithm. …”
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AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…ObjectiveTo address the challenges of complex underwater environments, particularly the uncertainties in ocean currents, this study proposes an improved sparrow search algorithm (ISSA) for autonomous underwater vehicles (AUVs) path planning. The goal is to enhance the efficiency and robustness of path planning by minimizing navigation time and improving path stability in uncertain conditions. …”
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Path Planning Algorithm for Manipulators in Complex Scenes Based on Improved RRT* by Xiqing Zhang, Pengyu Wang, Yongrui Guo, Qianqian Han, Kuoran Zhang

“…Aiming at the problems of a six-degree-of-freedom robotic arm in a three-dimensional multi-obstacle space, such as low sampling efficiency and path search failure, an improved fast extended random tree (RRT*) algorithm for robotic arm path planning method (abbreviated as HP-APF-RRT*) is proposed. …”
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Design of path planning robot simulator by applying sampling based method by Heru Suwoyo, Julpri Andika, Andi Adriansyah

“…The level of computational efficiency, path optimality, and the ability to adapt to variant environments are some of the issues that still arise, although these techniques have shown good results in many cases. …”
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Complete Coverage Path Planning Strategy for Reconfigurable Robot With Variable Footprint by Qinrui Tang, Lim Yi, Ash Yaw Sang Wan, Abdullah Aamir Hayat, Anh Vu Le, Mohan Rajesh Elara

“…To address this issue, we propose the Depth-First Search (DFS) for Complete Coverage Path Planning Strategy (CCPPS) for ECVWRs. This method allows adjustments to the generation of waypoints in CCPPS, minimizing the path length. …”
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Path planning of unmanned ships based on A* and dynamic window approach by FU Long, SHEN Zhen, TAO Hao, HAN Yunjun, DONG Xisong, XIONG Gang

“…To address the challenge of balancing global optimization, efficiency, and safety in path planning, a method that integrates global search and local optimization was proposed, based on the A* algorithm and the dynamic window approach (DWA). …”
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Task allocation and path planning for multi-robot systems in intelligent warehousing by CHU Jing, TIAN Yiqiu, YUE Qi, HUANG Yong

“…In this context, this paper aims to design a task allocation and path planning strategy for a multi-robot warehouse system to efficiently accomplish mixed single-robot and multi-robot types of warehouse tasks. …”
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Optimizing Sampling Points and Path Planning for Soil Monitoring in Agricultural Land by Jing Wang, Zhiqiang Zhai, Guangdong Xu, Ruoyu Zhang, Xin Zhang, Rong Hu

“…Furthermore, when the number of mixing points is large and the plot area is extensive, sampling efficiency is significantly reduced. In this study, an automated method for establishing the layout of sampling points and a threshold-based mixed path planning algorithm are proposed. …”
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Q-learning global path planning for UAV navigation with pondered priorities by Kevin B. de Carvalho, Hiago de O.B. Batista, Leonardo A. Fagundes-Junior, Iure Rosa L. de Oliveira, Alexandre S. Brandão

“…The method optimizes three pivotal factors: path length, safety, and energy consumption. By effectively balancing exploration and exploitation, this technique enables an autonomous agent to efficiently navigate from any initial point to a specified destination on the map. …”
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Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption by Yong Zhang, Lei Shi, Jing Chen, Xuefeng Li

“…The application of automated vehicles in logistics can efficiently reduce the cost of logistics and reduce the potential risks in the last mile. …”
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Research on Hybrid A* Based Path Optimization of Unmanned Mine Truck by DENG Mukun, LIU Yong, HUANG Jiade, LUO Yu

“…The results of simulation comparison test and on site vehicle test show that the proposed method can significantly improve the applicability and smoothness of the search path by the traditional hybrid A* algorithm, and the optimization efficiency is better than the traditional discrete point optimization.…”
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Position Selection and Collision-Free Path Planning for Fruit Picking Robots by Yonghee Cho, Dongwoon Choi, Kwangeun Ko, Jong Hyeon Park

“…This paper proposes an algorithm for selecting the position of a mobile manipulator for fruit harvesting using an inverse reachability map to achieve automation and enhance efficiency. Additionally, a method for collision-free path planning in joint space using the model predictive artificial potential field (MPAPF) algorithm is proposed. …”
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Prioritized Experience Replay–Based Path Planning Algorithm for Multiple UAVs by Chongde Ren, Jinchao Chen, Chenglie Du

“…Although UAVs working together on complicated jobs can significantly increase productivity and reduce costs, they can cause major issues with path planning. In complex environments, the path planning problem, which is a multiconstraint combinatorial optimization problem and hard to settle, requires considering numerous constraints and limitations and generates the best paths for each UAV to accomplish group tasks. …”
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