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A Fast Incremental Algorithm for Maintaining Dispatchability of Partially Controllable Plans

机译:维持部分可控计划的可分配性的快速增量算法

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Autonomous systems operating in real-world environments must be able to plan, schedule, and execute missions while robustly adapting to uncertainty and disturbances. Previous work on dispatchable execution increases the efficiency of plan execution under uncertainty by introducing a temporal plan dispatcher that schedules events dynamically in response to disturbances, and a compiler that reduces a plan to a dispatchable form that enables real-time scheduling. However, mis work does not address the situation where response requires modifying the plan in real-time. In these situations, after the autonomous system replans, compilation to dispatchable form must occur in near real-time. The key contribution of this paper is a fast Incremental Dynamic Control algorithm (IDC) for maintaining the dispatchability of a partially controllable plan, in response to incremental plan modifications by an online planner. IDC is developed as a set of incremental update rules that exploit the structure of the plan in order to efficiently propagate the effects of constraint loosening and tightening throughout the plan. IDC exhibits an order of magnitude improvement in compile time over the state of the art non-incremental algorithm applied to randomly generated problems. Its practicality is demonstrated on plans for coordinating rovers within the authors' hardware test-bed.
机译:在现实环境中运行的自治系统必须能够计划,安排和执行任务,同时能够强大地适应不确定性和干扰。先前有关可调度执行的工作通过引入临时计划调度程序来提高计划在不确定性下的效率,该临时调度程序可根据干扰动态地调度事件,而编译器则可将计划缩减为可调度的形式以实现实时调度。但是,工作不当并不能解决响应需要实时修改计划的情况。在这些情况下,自治系统重新计划后,必须几乎实时地进行编译成可调度的形式。本文的主要贡献是一种快速的增量动态控制算法(IDC),用于响应在线计划人员对增量计划进行的修改来维持部分可控计划的可调度性。 IDC是作为一组增量更新规则开发的,这些规则利用计划的结构来有效地在整个计划中传播约束放松和收紧的影响。与应用于随机生成问题的非增量算法相比,IDC的编译时间提高了一个数量级。在作者的硬件测试平台上协调流动站的计划中证明了其实用性。

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