搜索资源列表
matlab-path-planning
- 机器人路径规划遗传算法matlab仿真源代码-Robot path planning simulation matlab genetic algorithm source code
matlab
- 蚁群算法tsp旅行商问题,讲述路径规划问题-Ant colony algorithm TSP
matlab(1)
- 节约算法,进行路径规划,含有时间窗,能够对路径进行优化-Saving algorithm, path planning, comprising time window, the path can be optimized for
lujingguihua
- 很好用的基于人工势场法做的matlab路径规划算法 仿真程序-Do based on artificial potential field method matlab well used path planning algorithm simulation program
栅格环境matlab源码
- 将数据信息转换为栅格地图,便于进行下一步的路径规划
MATLAB
- 基于蚁群算法的机器人路径规划MATLAB源码 -Ant colony algorithm based robot path planning MATLAB source
matlab
- 人工势场法的路径规划方面的编程代码,能够很好地实现避障,对学习有一定帮助-Path planning artificial potential field programming code, can achieve a good obstacle avoidance, to learn of some help
matlab-code
- 给予遗传算法的航迹规划和路径规划算法,含全部源程序,提供大家共同学习-Route planning and path planning algorithm given genetic algorithm, including all source code, provided we learn together
Matlab
- 针对经典Dijkstra算法时间复杂度问题,提出双向Dijkstra搜索算法解决智能交通路径规划问题,并通过仿真实验验证了算法的可行性和有效性(英文版资料)-Typical shortest path is Dijkstra algorithm, its time complexity is O (n 2 ). A map of the city’s road network has many nodes, if we use the Dijkstra algorithm, the time
Matlab
- 为了提高四足机器人在复杂环境下的适应性,重点研究了采用飞行时间(TOF)原理相机的四足机器人环境感知策略并改进了地形识别及路径规划算法.首先采用高斯过程回归(GPR)模型对TOF相机的距离数据进行误差校正,解决了采用传统多项式或三角函数模型进行误差修正时模型阶次过高及函数组合复杂的问题.基于得到的环境深度信息,采用数字高程模型(DEM)进行地形描述,并通过计算各栅格的坡度、粗糙度、起伏度对地形进行识别.粗糙度由该栅格所处的坡度平面与其8邻域高程点的离散程度进行计算,避免了采用高程方差计算时对粗糙
matlab-VRP
- 物流路径规划,节约里程法的matlab实现-Logistics path planning, the MATLAB realization of the economical mileage method
matlab-QLEARNING
- 模拟机器人路径规划,采用强化学习中的Q学习算法来实现,最后会返回机器人选择路径的坐标位置-code for path searching
MATLAB
- 时序差分学习是强化学习的一种重要算法,该代码提供了时序差分学习做路径规划的一个仿真。-Temporal difference learning is an important algorithm for reinforcement learning, which provides a simulation of sequential differential learning for path planning.
Q-Learing-path-planning-MATLAB
- 基于增强学习Q-learning方法的路径规划matlab仿真程序-Based on the enhanced learning Q-learning method of path planning matlab simulation program
基于Hopfield神经网络的旅行商优化计算
- 实现最短路径选择问题 运用MATLAB神经网络算法(Achieve the shortest path choice)
A star
- 使用A star算法进行路径规划。。matlab代码。。。。。。(Path planning using the A star algorithm)
Dijkstra-master
- Dijkstra算法,解决机器人的路径规划问题,使用的程序语言为matlab语言。(This is the Dijkstra algorithm. It can solve the robot path planning problem, and the result is good. The programming language used is the MATLAB language.)
show11
- 基于A*算法的最优路径规划的matlab仿真(Matlab simulation of optimal path planning based on A* algorithm)
ant. MATLAB
- 蚁群算法在机器人路经规划中MATLAB栅格地图求得最短路径(Robot path planning MATLAB ant colony algorithm to find the shortest path in the grid map)
RRT-star-master
- RT(快速扩展随机树)是一种基于采样的算法求解路径规划问题。RRT提供可行的解如果时间RRT趋于无穷大。 RRT *是一个基于采样的算法为解决运动规划问题,这是一个概率最优变异性。RRT *收敛到最优解的渐近。 RRT * FN是一个基于采样的算法基于RRT *。RRT * FN内在渐近收敛到最优解,然而RRT * FN实现使用更少的内存(RRT (Rapidly-Exploring Random Tree) is a sampling-based algorithm for solving