共查询到19条相似文献,搜索用时 203 毫秒
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基于神经网络的水下机器人运动预测控制方法 总被引:2,自引:1,他引:1
将神经网络和模糊理论应用于水下机器人运动规划和控制中,提出了能实现模拟控制规则的基于强化学习的自学习和自调整的规划算法,设计了水下机器人实时运动规划器结构以及规划器操作过程,提出了基于预测模糊控制进行水下机器人运动控制的方法。在计算机仿真状态下,实现了对水下机器人这一复杂非线性系统的预测控制,仿真实验结果验证了本文所提的方法的有效性。 相似文献
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大范围环境下自主式水下潜器两种全局路径规划方法的研究 总被引:1,自引:1,他引:0
应用遗传算法(GA)和A·算法对自主式水下潜器(简称AUV)在大范围海洋环境中的全局路径规划问题进行了研究.介绍了基于栅格的环境模型及其数据结构,讨论了GA的染色体编码方式、基于知识的初始种群生成方法与适应度函数,基于领域知识设计了五种遗传算子,给出了A·算法的具体实现方法.通过仿真结果可以看出:GA采用可变长编码方式使路径描述简单、清晰,具有收敛速度快、求解实际问题效率高的特点;A*算法可在较短时间内求得相对栅格优化的路径.两种算法均可满足系统实时性要求. 相似文献
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针对经典人工蜂群算法在机器人路径规划中易于陷入局部极值,且寻优过程收敛速度较慢等问题,提出了一种基于约束优化的改进人工蜂群算法.通过设计变异算子来增大极值在陷入局部最优时的跳出概率,提高机器人路径规划的收敛能力.在机器人路径规划上,对文中方法、遗传算法、A*算法以及经典人工蜂群算法进行性能评估.实验结果表明,文中方法能有效避免路径规划中的局部极值,减少机器人路径规划时间损耗,提高了路径规划效率. 相似文献
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自主/遥控水下机器人(ARV)是一种综合自主水下机器人和遥控水下机器人特点的新型水下机器人,融合ARV自主控制和操作人员遥控的共享控制是ARV控制的关键问题。针对ARV在环境探索任务中和目标观察任务中的共享控制,采用基于行为的控制思想,提出一种基于行为的ARV共享控制方法,包括实现环境探索的遥控行为、自主避障行为、以及实现目标观察的人机协同路径跟踪控制行为,通过设计的基于优先级的行为组织和融合方法,实现了ARV基于设计的行为以"人主机辅"模式执行环境探索继而以"机主人辅"模式执行目标观察过程的有效共享控制。基于构建的水下机器人共享控制仿真环境对设计的共享控制方法进行仿真实验,验证了提出的共享控制方法的有效性。 相似文献
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针对现有的离散生物启发神经网络(Glasius bioinspired neural networks, GBNN)算法在未知环境下,存在的路径规划时间长、易陷入局部最优等问题,提出一种结合A*与GBNN模型的改进算法。在GBNN活性值栅格网络中,算法将各栅格的活性值作为A*的代价函数进行运算并使用跳点搜索规则优化,实现未知环境下的实时路径规划。仿真实验结果表明,该算法有效改善了自主水下航行器在未知环境下的寻路效率,可以满足自主水下航行器实时路径规划需求。 相似文献
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An autonomous underwater vehicle (AUV) must use an algorithm to plan its path to distant, mobile offshore objects. Because
of the uneven distribution of obstacles in the real world, the efficiency of the algorithm decreases if the global environment
is represented by regular grids with all of them at the highest resolution. The framed quadtree data structure is able to
more efficiently represent the environment. When planning the path, the dynamic object is expressed instead as several static
objects which are used by the path planner to update the path. By taking account of the characteristics of the framed quadtree,
objects can be projected on the frame nodes to increase the precision of the path. Analysis and simulations showed the proposed
planner could increase efficiency while improving the ability of the AUV to follow an object. 相似文献
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《船舶与海洋工程学报》2018,(4)
Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner. 相似文献
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针对全局路径规划研究中遗传算法存在搜索范围广而导致收敛速度慢的问题,本文提出一种混合优化的全局路径规划方法,完成对图像读取、处理后使用A*算法预处理缩小可行区域从而提高收敛速度。所提出的混合优化规划方法主要优化遗传算法的初始种群,在不影响最终路线的情况下,缩小初始种群的搜索范围,提高算法进行全局路径规划的速度,快速有效的规划出全局路线。另外本文给出一种评价体系对规划结果进行定量的避障评价,评价结果能够以数值形式对规划结果进行综合评价,评价结果显示通过混合优化算法规划出的路径具有更佳的安全性。 相似文献
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ZHANGJing-juan LIXue-lian HAOYan-ling 《船舶与海洋工程学报》2003,2(1):60-65
A new algorithm is proposed for underwater vehicles multi-path planning. This algorithm is based on fitness sharing genetic algorithm, clustering and evolution of multiple populations, which can keep the diversity of the solution path, and decrease the operating time because of the independent evolution of each subpopulation. The multi-path planning algorithm is demonstrated by a number of two-dimensional path planning problems. The results show that the multi-path planning algorithm has the following characteristics: high searching capability, rapid convergence and high reliability. 相似文献
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ZHANGMing-jun HANZhi-xue 《船舶与海洋工程学报》2004,3(1):46-51
In this paper we present two strategies of AUV (Autonomous Underwater Vehicle) region detection and an approach to decompose the detection region according to the direction of the ocean current. In the task of local detection and identification, the algorithm against the ocean current was proposed. In the tasks of closing obstacle, going back or moving, the fuzzy logic theory was used to solve the effect of ocean current. In one of our strategies the concept of weighted journey based on the angle between heading and ocean current is suggested and the TSP‘s exact optimal result is utilized to solve the global path planning. Simulations demonstrate the feasibility of this approach. 相似文献
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[目的]针对微小型欠驱动自主式水下机器人(autonomous underwater vehicle,AUV)集群控制问题,设计一种基于改进RRT^(*)算法的编队控制策略。[方法]RRT^(*)算法规划的路径陡变难以跟踪且收敛速度较慢,针对该问题提出改进方法。首先加入偏置函数使随机采样点靠近目标点,然后采用Dubins曲线平滑连接采样点,通过在可变半径范围内重新布线,并设计有关曲线长度与避障的代价函数,选择最优路径。依据代价和最小值为多AUV分配集结点,协调多AUV速度完成最小集结时间约束,随后设计基于Dubins路径的分段向量场构造方法,使得多AUV跟踪规划路径,到达目标集结点时速度与方向保持一致。[结果]仿真结果表明,多AUV编队平均路径长度缩短26.6%,平均集结时间缩短21.7%。[结论]该算法路径规划质量高,可顺利完成编队集结任务。 相似文献