Online path planning based on MILP for unmanned surface vehicles
Leng J(冷静); Liu J(刘健); Xu HL(徐红丽)
2013
会议名称OCEANS 2013 MTS/IEEE San Diego Conference: An Ocean in Common
会议日期September 23-26, 2013
会议地点San Diego, CA, United states
关键词Algorithms Embedded systems Linear programming Mathematical transformations Oceanography
页码1-7
中文摘要This paper presents an algorithm for online path planning of USVs to navigate safely in dynamic, sophisticated environments of oceans. The proposed algorithm is based on Mixed Integer Linear Programming (MILP) which integrated with Velocity Obstacle (VO) approach. MILP is an optimization method under multiple constraint conditions of objective function maximization or minimization. The constraints of environment and maneuverability all can be considered and appended to the constraints conditions expressed in the form of inequality. The objective function and constraint conditions are required in linear by MILP, however, the motion of USV and its path planning are nonlinear. So the principle problem is to transform the nonlinear problem into the linear problem. On the other hand, VO makes a linear prediction, which is well appended into the constraint conditions. MILP has advantages in astringency, optimization, real-time and VO also has the advantages in real-time. The combination of MILP and VO utilized the advantages of rapidity of computations, which is well suited for embedded system of robotic applications. The algorithm is demonstrated via simulation with more safety and acclimation in sophisticated environments of oceans.
收录类别EI ; CPCI(ISTP)
产权排序1
会议录OCEANS 2013 MTS/IEEE; San Diego: An Ocean in Common
会议录出版者IEEE Computer Society
会议录出版地Washington, DC
语种英语
WOS记录号WOS:000334165801035
内容类型会议论文
源URL[http://ir.sia.cn/handle/173321/14572]  
专题沈阳自动化研究所_海洋信息技术装备中心
推荐引用方式
GB/T 7714
Leng J,Liu J,Xu HL. Online path planning based on MILP for unmanned surface vehicles[C]. 见:OCEANS 2013 MTS/IEEE San Diego Conference: An Ocean in Common. San Diego, CA, United states. September 23-26, 2013.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace