林昌龙, 刘开周, 李一平, 张忆文, 陈雁. 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. DOI: 10.13973/j.cnki.robot.190227
引用本文: 林昌龙, 刘开周, 李一平, 张忆文, 陈雁. 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. DOI: 10.13973/j.cnki.robot.190227
LIN Changlong, LIU Kaizhou, LI Yiping, ZHANG Yiwen, CHEN Yan. Bearing-only Target Pursuing Strategy for AUV Based on Short-term Planning[J]. ROBOT, 2020, 42(3): 309-315. DOI: 10.13973/j.cnki.robot.190227
Citation: LIN Changlong, LIU Kaizhou, LI Yiping, ZHANG Yiwen, CHEN Yan. Bearing-only Target Pursuing Strategy for AUV Based on Short-term Planning[J]. ROBOT, 2020, 42(3): 309-315. DOI: 10.13973/j.cnki.robot.190227

基于短期规划的AUV纯方位目标追踪策略

Bearing-only Target Pursuing Strategy for AUV Based on Short-term Planning

  • 摘要: 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.

     

    Abstract: The problem of pursuing large marine mammals by autonomous underwater vehicles (AUVs) is studied. Because the maneuverability of the target is much better than that of the tracker, the AUV may miss the opportunity of approaching 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.

     

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