Motion planning for an under-actuated autonomous underwater vehicle based on fast marching nonlinear model-predictive quantum particle swarm optimization
Motion planning for an under-actuated autonomous underwater vehicle based on fast marching nonlinear model-predictive quantum particle swarm optimization
复制标题
基于快速行进非线性模型预测量子粒子群优化的欠驱动自主水下航行器运动规划
DOI：
10.1016/j.oceaneng.2022.113391
复制
发表时间：
2023-01
影响因子：
5
通讯作者：
Zhu Daqi
中科院分区：
文献类型：
--
作者：
Chen Mingzhi;Guo Shuxuan;Zhu Daqi
运动规划器决定了自主水下航行器的自主性。然而，许多研究往往忽略了自主水下机器人和水下环境的特点，导致轨迹不合理。针对这一问题，本文结合自主式水下机器人的特点，通过预测和优化对水下机器人的运动力进行规划。考虑到水下环境的特殊性，对快速旅行算法进行了修改，以利用有利的电流和输出到达时间。提出了一种新的目标函数，它包含了到达时间来暗示避障和距离优化的要求。在目标函数中加入惩罚项以避免强侧流。同时，还将力及其变化率限制在适当的范围内，以平衡能量消耗。为了满足实际应用中对运行时间的高要求，将热启动改进量子粒子群算法引入力优化中。在自主研制的水下机器人上进行了仿真研究。该方法在多岛屿地区、海流、动态三维环境中具有良好的应用效果。仿真结果表明，该规划器具有较好的鲁棒性和适应性。
The motion planner determines the autonomy of the autonomous underwater vehicle. However, many studies often ignore the characteristics of autonomous underwater vehicles and the underwater environment, resulting in unreasonable trajectories. To solve this problem, this paper plans the motion force through prediction and optimization to integrate the characteristics of the autonomous underwater vehicle. The fast travel algorithm is modified to take advantage of favorable currents and output arrival times, taking into account the peculiarities of the underwater environment. A novel objective function is proposed, which incorporates the arrival times to imply the requirements of obstacle avoidance and distance optimization. A penalty item is included in the objective function to avoid strong side flow. At the same time, the force and its changing rate limited in appropriate ranges are also included to balance energy consumption. In order to meet the high running time requirements in practical applications, the warm-start improved quantum particle swarm optimization is introduced into force optimization. Simulation studies are performed on a self-developed autonomous underwater vehicle. The method has good application effects in multi-island areas, ocean currents, and dynamic three-dimensional environments. Comparative simulations show that the planner plans shorter paths with good robustness and adaptability.
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DOI：
10.1109/tnnls.2020.3042120
发表时间：
2022-04-01
影响因子：
10.4
作者：
Chai, Runqi;Tsourdos, Antonios;Chen, C. L. Philip
通讯作者：
Chen, C. L. Philip
影响因子：
14.4
作者：
Koenig, S;Likhachev, M;Furcy, D
通讯作者：
Furcy, D
DOI：
--
发表时间：
2016-04
期刊：
ArXiv
影响因子：
--
作者：
S. M. Zadeh;A. Yazdani;K. Sammut;D. Powers
通讯作者：
S. M. Zadeh;A. Yazdani;K. Sammut;D. Powers
DOI：
10.25043/19098642.40
发表时间：
2010-07
期刊：
--
影响因子：
--
作者：
C. Caldwell;D. Dunlap;E. Collins
通讯作者：
C. Caldwell;D. Dunlap;E. Collins
DOI：
10.1109/fskd.2017.8393137
发表时间：
2017-07
期刊：
2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
影响因子：
--
作者：
J. Ni;Zhitong Zhang;Baiyan Su;Xinnan Fan;Wei Liang
通讯作者：
J. Ni;Zhitong Zhang;Baiyan Su;Xinnan Fan;Wei Liang