Showing 201 - 220 results of 571 for search 'path optimization algorithm', query time: 0.22s Refine Results
  1. 201

    Enhanced USV path planning through integrated Bi-RRT and DWA algorithms considering environmental factors by Yanghua Zhou (20449441)

    Published 2024
    “…Through enhancements in node expansion techniques, Improvements in Tree Expansion to eliminate redundancy, and improvements in Sample Point Generation to augment the Bi-RRT algorithm, the algorithm achieves heightened search efficiency and path security, ultimately leading to the derivation of globally optimal trajectories. …”
  2. 202

    <b>D-Star-based Optimized Trajectory Planner for </b><b>Mobile Robots Operating in Dense </b><b>Environments</b> by Andrey Vukolov (19730578)

    Published 2024
    “…It contains the description of the novel <a href="https://wiki.ros.org" rel="noreferrer" target="_blank">ROS</a> module that implements the adopted version of the known and well-described D-star (D*) algorithm. It is accompanied by a customised heuristic, an optimizer pipeline for trajectory decompaction, and a postprocessing engine for holding a safe distance from the obstacles. …”
  3. 203

    Dual exit planning total path length. by Tiechao Liu (20396420)

    Published 2024
    “…The artificial potential field is integrated into the ant colony algorithm, and combined with the extended Moore type cellular automata, an extended cellular automata model based on the potential field ant colony algorithm is proposed to optimize the calculation of personnel evacuation and path planning in the evacuation area. …”
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    Data Sheet 1_A modified A* algorithm combining remote sensing technique to collect representative samples from unmanned surface vehicles.docx by Lei Wang (6656)

    Published 2024
    “…Water quality parameters were initially retrieved using satellite remote sensing imagery and a deep belief network model, with the parameter value incorporated as coefficient Q in the heuristic function of A* algorithm. The adjustment coefficient k was then introduced into the coefficient Q to optimize the trade-off between sampling representativeness and path length. …”
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