Showing 41 - 60 results of 245 for search '"path planning"', query time: 0.05s Refine Results
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    A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning by Junqi Yu, Ruolin Li, Zengxi Feng, Anjun Zhao, Zirui Yu, Ziyan Ye, Junfeng Wang

    Published 2020-01-01
    “…In order to improve the working efficiency of automated guided vehicles (AGVs) and the processing efficiency of fulfilling orders in intelligent warehouses, a novel parallel ant colony optimization algorithm for warehouse path planning is proposed. Through the interaction of pheromones among multiple subcolonies, the coevolution of multiple subcolonies is realized and the operational capability of the algorithm is improved. …”
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    Article
  3. 43

    Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment by Yong-feng Dong, Hong-mei Xia, Yan-cong Zhou

    Published 2016-01-01
    “…In the smart home environment, aiming at the disordered and multiple destinations path planning, the sequencing rule is proposed to determine the order of destinations. …”
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    Article
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    Research of the Path Planning of Mobile Robot based on Improved Ant Colony Algorithm by Yu Yong

    Published 2016-01-01
    Subjects: “…Mobile robot path planning…”
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    Article
  7. 47

    A New Real-Time Path Planning Method Based on the Belief Space by Yu-xin Zhao, Xin-an Wu, Yan Ma

    Published 2013-01-01
    “…A new approach of real-time path planning based on belief space is proposed, which solves the problems of modeling the real-time detecting environment and optimizing in local path planning with the fusing factors. …”
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    Article
  8. 48

    Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing by Zhi-qiang Liu, Teng Zhang, Yi-fan Wang

    Published 2019-01-01
    “…A local dynamic path planning method is proposed to compensate for the lack of consideration of the movement state of surrounding vehicles, the poor comfort, and the low traffic efficiency when the existing vehicle changes lanes automatically. …”
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    Article
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    Volcanic Ash Region Path Planning Based on Improved A-Star Algorithm by Lan Ma, Haotong Zhang, Shijun Meng, Jiayue Liu

    Published 2022-01-01
    “…In civil aviation flight path planning, in order to effectively reduce the safety threat caused by the volcanic ash area to the civil aviation flight, factors such as the speed and acceleration of the aircraft in the volcanic ash area must be considered. …”
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    Article
  12. 52

    OPTIMIZING AUTONOMOUS VEHICLE PATH PLANNING USING REINFORCEMENT LEARNING AND DYNAMIC MAPPING by Sundaram Arumugam, Frank Stomp

    Published 2024-12-01
    “…Path planning is essential for autonomous driving, enabling secure and effective navigation in intricate and dynamic settings. …”
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    Article
  13. 53

    Improved Manipulator Obstacle Avoidance Path Planning Based on Potential Field Method by Ming Zhao, Xiaoqing Lv

    Published 2020-01-01
    “…Aiming at the existing artificial potential field method, it still has the defects of easy to fall into local extremum, low success rate and unsatisfactory path when solving the problem of obstacle avoidance path planning of manipulator. An improved method for avoiding obstacle path of manipulator is proposed. …”
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    Article
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    Evaluating and refining undersea cable path planning algorithms: A comparative study. by Tianjiao Wang, Zengfu Wang, Bill Moran, Xinyu Wang, Moshe Zukerman

    Published 2024-01-01
    “…This paper compares three automated path-planning algorithms based on publicly available data. …”
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    Article
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    Multi-Objective Dynamic Path Planning with Multi-Agent Deep Reinforcement Learning by Mengxue Tao, Qiang Li, Junxi Yu

    Published 2024-12-01
    Subjects: “…multi-objective dynamic path planning…”
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    Article
  19. 59

    Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system by Shengwu Zhao, Lei Shi, Wenzhe Zhang, Zhihong Deng

    Published 2021-10-01
    “…To deal with such problems, this work improves the global static path‐planning algorithm based on the A* algorithm, and the local dynamic path‐planning algorithm based on dynamic window approach (DWA). …”
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