Dynamic path planning with multi-agent data fusion - The Parallel Hierarchical Replanner
Dynamic path planning with multi-agent data fusion - The Parallel Hierarchical Replanner
复制标题
多智能体数据融合的动态路径规划 - 并行分层重新规划器
DOI：
10.1109/robot.2009.5152883
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
S. Scheding
中科院分区：
文献类型：
--
作者：
Thomas Allen;A. Hill;J. Underwood;S. Scheding
提出了分层规划系统的设计，其中每个级别并行操作并异步通信。结果表明，这种并行分层重新规划器既是反应性的，又在给定有限计算能力的情况下尽可能接近状态空间中所有信息的最佳状态。与其他三种分层方法的比较表明，对于实现任务目标所需的时间比所产生的成本更重要的场景，该方法比文献中的相关方法具有更好的性能。
The design of a hierarchical planning system in which each level operates in parallel and communicates asynchronously is presented. It is shown that this Parallel Hierarchical Replanner is both reactive, and as close to optimal over all information in the state space as is possible given finite computational power. A comparison with three other hierarchical methods is presented, which demonstrates that for scenarios in which the time taken to achieve a mission goal is of greater importance than the cost incurred, this approach has better performance than related methods in the literature.