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Rapid replanning of energy-efficient paths for navigation on uneven terrains

机译:快速重新规划能效路径,以在不平坦的地形上导航

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Mobile robots are often utilized in remote and hostile outdoor environments with uncertainties and unknown dangerous. The energy-efficient paths generated based on prior information can be impracticable due to the changes in the environment. Recently proposed Z∗ search algorithm is capable of finding physically feasible energy-efficient paths on uneven terrains. It can achieve the same accuracy as any brute force algorithm, but with a low computational complexity. However, neither Z∗ nor any other energy-efficient path planners can effectively handle path replanning triggered by environment changes such as emergence of obstacles. In order to fill this void, we propose a novel algorithm which can recompute optimal paths efficiently. Simulation results show that the proposed algorithm can find equally energy-efficient paths as Z∗ does, but at a considerably lower computational cost. Therefore, the proposed algorithm can be very useful in mobile robot navigation on uneven terrains with unknown obstacles.
机译:移动机器人通常在不确定和未知危险的偏远和敌对的室外环境中使用。由于环境的变化,基于先验信息生成的节能路径可能不可行。最近提出的Z *搜索算法能够在不平坦的地形上找到物理上可行的节能路径。它可以达到与任何蛮力算法相同的精度,但是计算复杂度较低。但是,Z ∗或其他任何节能路径规划者都无法有效处理由环境变化(例如障碍物的出现)触发的路径重新规划。为了填补这一空白,我们提出了一种可以有效地重新计算最优路径的新颖算法。仿真结果表明,所提出的算法可以找到与Z ∗相同的节能路径,但计算成本却低得多。因此,所提出的算法在障碍物未知的不平坦地形上的移动机器人导航中非常有用。

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