摘要
为提高自主式水下机器人(AUV)在复杂环境、任务多变及通信受限等恶劣条件下的自适应性、自处理能力和自身安全可靠性,首先,针对不同层次分别研究了基于与或分解树的使命规划、基于有限状态机的任务规划和基于插入删除调整的行为规划方法;然后,设计了分层重规划监督决策的具体算法;最后,通过相关实验,验证了所设计的分层体系结构及其分层规划与分层重规划监督决策方法,能明显提高AUV自主任务完成效果和满足不确定事件自处理时的时效性要求.
In order to improve the adaptability,self-processing capacity and safety reliability of autonomous underwater vehicle(AUV)in the complex environment,the mission planning based on the andor decomposition tree,task planning were studied and designed based on the finite state machine and behavior planning based on the insert or delete adjustment for different levels.Then,the algorithm of hierarchical re-planning and supervision decision were designed.Finally,the related experiment showes that the designed hierarchical architecture,planning and re-planning supervision or decision methods can significantly improve the task effect of AUV and meet the requirements of times in processing the uncertain events.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第S1期77-80,共4页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(60975071)
大连民族学院人才引进科研启动基金资助项目
关键词
水下机器人
体系结构
分层规划
重规划
监督决策
autonomous underwater vehicle
architecture
hierarchical planning
re-planning
supervision or decision
