Planning,monitoring and replanning techniques for handling abnormity in HTN-based planning and execution

A framework that integrates planning,monitoring and replanning techniques is proposed.It can devise the best solution based on the current state according to specific objectives and properly deal with the influence of abnormity on the plan execution.The framework consists of three parts:the hierarchical task network(HTN)planner based on Monte Carlo tree search(MCTS),hybrid plan monitoring based on forward and backward and norm-based replanning method selection.The HTN planner based on MCTS selects the optimal method for HTN compound task through pre-exploration.Based on specific objectives,it can identify the best solution to the current problem.The hybrid plan monitoring has the capability to detect the influence of abnormity on the effect of an executed action and the premise of an unexecuted action,thus trigger the replanning.The norm-based replanning selection method can measure the difference between the expected state and the actual state,and then select the best replanning algorithm.The experimental results reveal that our method can effectively deal with the influence of abnormity on the implementation of the plan and achieve the target task in an optimal way.

基于rPPG的心率测量方法研究

为了解决传统穿戴式心率测量设备的不便,对以摄像头采集的视频数据进行研究处理,并进行一系列相关实验。采用自动获取感兴趣区域,并利用算法对区域进行校正。使用独立成分分析提取含有脉搏波信号,实现心率检测。结果表明,在提取脉搏波信号时,可以成功将信号从视频数据中提取出来,在未来医疗行业、家庭监测中有着较大的发展前景。

层次任务网络中的重新规划研究综述

层次任务网络(hierarchical task network,HTN)作为智能规划技术的重要组成部分,已成功应用于无人平台任务规划、应急方案制定等各领域中。由于日益增加的不确定因素对计划执行效果的影响,迫切需要重新规划技术,因此基于HTN的重新规划技术成为近年来的研究热点。首先,通过对当前研究现状的总结梳理,提出了基于HTN的3层重新规划框架。然后,分别从框架中的计划修复、局部重规划和全局重规划3个层次阐述了相应的技术路线与实现细节,针对不同层次指出了目前方法的优势与不足。最后,对该问题未来的研究方向进行了展望,并提出了待解决的关键问题及解决思路。

基于HTN的混合式作战计划监视与重规划方法研究

信息化时代,战场态势瞬息万变,如何根据快速变化的战场态势对作战计划快速调整,是作战任务规划研究的关键。提出了一种基于层次任务网的混合式计划监视与重规划方法,依据效果期望与任务期望监视计划的执行,确定计划调整的时机。基于范数度量计划执行与两种期望的差异,根据差异的大小选择不同的重规划算法。实验评估表明,所提方法能够提升计划执行中应对不确定因素的能力,为不确定环境下的计划执行与调整提供了有效的解决方案。