基于微重启和部分客观马尔可夫决策模型的智能水下机器人软件自修复方法  

Self-repair method for autonomous underwater vehicle software based on micro-reboot and partially observable Markov decision process model

作　　者：张汝波 孟雷[1] 史长亭[1] 

机构地区：[1]哈尔滨工程大学计算机科学与技术学院,哈尔滨150001 [2]大连民族大学机电工程学院,辽宁大连116600

出　　处：《计算机应用》2015年第8期2375-2379,共5页journal of Computer Applications

基　　金：装备预研基金项目(9140C270101130C27099)

摘　　要：针对智能水下机器人(AUV)软件故障修复过程中存在的修复代价过高和系统环境只有部分可观察的问题,提出了一种基于微重启技术和部分客观马尔可夫决策(POMDP)模型的AUV软件故障修复方法。该方法结合AUV软件系统分层结构特点,构建了基于微重启的三层重启结构,便于细粒度的自修复微重启策略的实施;并依据部分可观马尔可夫决策过程理论,给出AUV软件自修复POMDP模型,同时采用基于点的值迭代(PBVI)算法求解生成修复策略,以最小化累积修复代价为目标,使系统在部分可观环境下能够以较低的修复代价执行修复动作。仿真实验结果表明,基于微重启技术和POMDP模型的AUV软件故障修复方法能够解决由软件老化及系统调用引起的AUV软件故障,同与两层微重启策略和三层微重启固定策略相比,该方法在累积故障修复时间和运行稳定性上明显更优。Aiming at the disadvantages of high fixing cost and partial observability of system environment in the process of repairing Autonomous Underwater Vehicle （AUV） software faults, a method was proposed based on micro-reboot mechanism and Partially Observable Markov Decision Process （POMDP） model for failure repair of AUV. To facilitate the implementation of the fine-grained self-repair micro-reboot strategy, a hierarchical structure was built based on micro-reboot combined with the characteristics of AUV software. Meanwhile, a self-repair model was put forward according to the theory of POMDP. With the goal of minimizing the fixing cost, the repair strategy was solved by Point Based Value Iteration （PBVI） algorithm to allow the repair action to execute in the partially observable environment at a lower cost. The simulation results show that the proposed repairing method can solve the AUV software failures caused by the software-aging and system calls. Compared with two-tier micro-repair strategy and three-tier micro-repair fixing strategy, this method is obviously superior to the contrast method in cumulative fault repair time and operational stability.

关 键 词：智能水下机器人 微重启 自修复 部分客观马尔可夫决策 基于点的值迭代算法 

分 类 号：TP311.52[自动化与计算机技术—计算机软件与理论]