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1)  artificial potential field(APF)
人工势场模型
2)  fuzzy artificial potential field
模糊人工势场
1.
Mobile robot path planning based on the fuzzy artificial potential field;
基于模糊人工势场的移动机器人路径规划
3)  artificial potential field
人工势场
1.
A path planning method for mobile robot based on artificial potential field;
基于人工势场法的机器人路径规划
2.
Navigation of mobile robot using improved artificial potential field method;
改进的人工势场法用于移动机器人导航
3.
Research on Reinforcement Learning Problem Based on Artificial Potential Field;
基于人工势场的激励学习问题研究
4)  potential field
人工势场
1.
The artificial potential field method is widely used for mobile robot path planning due to its simplicity and mathematical analysis,However,most reaserches have been focused on solving the path planning in a stationary environment where both targets and obstacles are stationary.
人工势场法由于其简单性和便于数学描述被广泛应用在移动机器人路径规划上,然而多数研究都集中在解决静态路径规划上,即目标和障碍物都是静态的。
2.
Secondly, this thesis introduces some popular methods for path planning, such as the global path planning methods, including artificial potential field, topology, visual graph and free-space method; including the local path planning methods, neural network, fuzzy logic and genetic algorithm and analyzes the advantages and weakpoints of these meth
其次,概括介绍了机器人路径规划的方法,包括全局路径规划方法:人工势场法,栅格法,拓扑法,可视图法,自由空间法,以及局部路径规划方法:神经网络法,模糊逻辑算法,遗传算法等。
5)  artificial potential
人工势场
1.
On the basis of building forward looking sonar view model and artificial potential model,decision control of AUV is made,objects are searched through grads approach,a collision free path is planed.
在建立前视声呐视域模型和人工势场模型的基础上,对AUV进行决策控制,通过梯度逼近法对目标进行搜索,快速规划出一条无碰撞的路径。
2.
The reinforcement learning is adopted to control and decision for AUV,and Q-learning,BP neural net,artificial potential is integrated to avoidance planning for AUV.
主要采用强化学习的方法对AUV进行控制和决策,综合Q学习算法、BP神经网络和人工势场法对AUV进行避碰规划。
3.
The reinforcement learning is adopted to control and decision for Autonomous Underwater Vehicles (AUV), and Q- learning , BP neural net, artificial potential is integrated to local plan for AUV.
主要采用强化学习的方法对自治水下机器人(AUV)进行控制和决策,综合Q学习算法、BP神经网络法、人工势场法对AUV进行局部路径规划。
6)  artificial potential field
人工势场法
1.
Research on artificial potential field for robot soccer path planning;
关于足球机器人路径规划中人工势场法的研究
2.
A path Planning of mobile robot based on improved artificial potential field method
一种基于改进人工势场法的移动机器人路径规划
3.
Path planning of cutting pipe fittings based on artificial potential field
基于人工势场法的管件切割路径规划
补充资料:模型势方法
分子式:
CAS号:

性质:又称模型势方法。即价电子从头计算法。其基本思想是,所研究体系的哈密顿算符仅显含价电子部分,而将原子内层的全部电子连同原子核构成的核实对外层价电子的作用用适当的模型势函数(即赝势pseudo potential)表示,同时引入表示投影算符的势以便将价电子波函数与内层电子波函数分离开来,然后对价电子进行变分并用自洽迭代处理,计算出价电子轨道波函数和能级值等。所引入的两个势均通过全电子的原子从头计算确定,随后用于分子计算。常见的赝势有两类,一类是基于固体物理理论的菲利普斯-克兰曼(Phillips-Kleinman)赝势原理发展起来的,一类是从早期的价电子概念出发,由赫律纳加(Huzinaga)等提出的模型。赝势方法主要用于含有重元素的化合物或原子簇的研究。

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