基于蛇优化算法的AUV搜索任务的层次规划方法
Zhiwen Wen1, Zhong Wang1, Xiangdong Wen2
1Xi'an Precision Machinery Research Institute, Xi'an 710077, China.
Sensors (Basel, Switzerland)
|November 27, 2024
概括
本研究介绍了一种对自动水下车辆 (AUV) 进行分层规划的方法,以快速拦截动态目标. 该方法优化了AUV导航时间和轨迹,以便在复杂环境中高效执行搜索任务.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 海洋工程 海洋工程
背景情况:
- 自主水下车辆 (AUV) 在动态战场环境中面临挑战,以拦截目标.
- 有效的全球自主规划对于AUV搜索任务的完成至关重要.
研究的目的:
- 开发一个分层的AUV任务规划方法,以尽量减少与动态目标相遇的时间.
- 处理初始目标信息可用的场景.
主要方法:
- 一种三级层次的层次编程方法与蛇优化算法相结合.
- 搜索任务的分解为外部 (遭遇时间),中间 (导航时间) 和内部 (轨迹优化) 层.
- 优化考虑诸如威胁区域,路径长度和路径平滑等约束因素.
主要成果:
- 拟议的方法通过对AUV搜索任务的模拟来验证.
- 在各种约束条件下对AUV进行有效的任务规划.
- 成功优化了AUV和动态目标之间的相遇时间.
结论:
- 层次规划方法为AUV动态目标搜索提供了可行和实用的解决方案.
- 该方法优化了AUV性能和碰撞时间,显示了重要的工程价值.
- 为类似水下无人系统的任务规划提供了有价值的参考.
相关概念视频
Optimal Foraging
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
Statically Indeterminate Problem Solving
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Heuristics
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
Optimization Problems
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
Methods of Medium Optimization
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...


