SIA OpenIR  > 水下机器人研究室
基于短期规划的AUV纯方位目标追踪策略
Alternative TitleBearing-only Target Pursuing Strategy for AUV Based on Short-term Planning
林昌龙1,2,3; 刘开周2,3; 李一平2,3; 张忆文1; 陈雁1
Department水下机器人研究室
Source Publication机器人
ISSN1002-0446
2020
Volume42Issue:3Pages:309-315
Contribution Rank1
Funding Organization国家自然科学基金(61403150,61802135) ; 机器人学国家重点实验室开放基金(2012-O02)
Keyword自主水下机器人 纯方位 目标追踪 行为规划
Abstract

对自主水下机器人(AUV)追踪海洋生物的问题进行研究,由于被追踪目标的机动能力远优于追踪者,待目标运动要素的估计值收敛之后再规划追踪的路径可能错过接近目标的时机.针对这个问题,借鉴博弈的思想提出了一种基于短期规划的目标追踪算法.该方法首先构建AUV在短期内所有可行的行为集合,然后对每一个行为能够达到的状态进行态势评估,最后选择使AUV处于最有利的追踪态势的行为作为规划的结果.为了检验该方法,开展了2组仿真实验:第1组实验显示本文方法的追踪成功率比传统方法提高了5.2%,第2组实验表明即使在较大的测量误差下AUV依然可以有效地追踪到目标.仿真结果表明该方法提高了AUV追踪到目标的成功率,并且具有较好的鲁棒性.

Other Abstract

The problem of pursuing large marine mammals by autonomous underwater vehicles (AUVs) is studied. Be- cause the maneuverability of the target is much better than that of the tracker, the AUV may miss the opportunity of approach- ing the target if it plans the pursuing path after the convergence of the target motion estimation value. Inspired by the idea of game theory, a target pursuing algorithm based on short-term planning is proposed to solve this problem. In this method, all feasible behaviors of AUV in a short period are firstly constructed, then the situation that the AUV will reach under each behavior is evaluated, and finally the behavior that makes AUV in the most advantageous pursuing situation is chosen as the result of planning. In order to examine this method, two simulation experiments are carried out: the first experiment shows that the pursuing success rate of the proposed method is 5.2% higher than that of the traditional method, and the second experiment shows that the AUV can still effectively pursue the target even under large measurement errors. The simulation results show that this method not only improves the success rate of pursuing but also has good robustness.

Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/26428
Collection水下机器人研究室
Corresponding Author林昌龙
Affiliation1.华侨大学计算机科学与技术学院
2.中国科学院沈阳自动化研究所机器人学国家重点实验室
3.中国科学院机器人与智能制造创新研究院
Recommended Citation
GB/T 7714
林昌龙,刘开周,李一平,等. 基于短期规划的AUV纯方位目标追踪策略[J]. 机器人,2020,42(3):309-315.
APA 林昌龙,刘开周,李一平,张忆文,&陈雁.(2020).基于短期规划的AUV纯方位目标追踪策略.机器人,42(3),309-315.
MLA 林昌龙,et al."基于短期规划的AUV纯方位目标追踪策略".机器人 42.3(2020):309-315.
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