rrt算法实现python
时间: 2023-08-27 11:06:33 浏览: 56
以下是一个简单的RRT算法的Python实现示例:
```python
import numpy as np
import matplotlib.pyplot as plt
class RRT:
def __init__(self, start, goal, obstacles, xlim, ylim, max_iter=1000, step_size=0.5):
self.start = start
self.goal = goal
self.obstacles = obstacles
self.xlim = xlim
self.ylim = ylim
self.max_iter = max_iter
self.step_size = step_size
self.nodes = []
def generate_random_node(self):
x = np.random.uniform(self.xlim[0], self.xlim[1])
y = np.random.uniform(self.ylim[0], self.ylim[1])
return np.array([x, y])
def find_nearest_node(self, point):
distances = [np.linalg.norm(point - node) for node in self.nodes]
nearest_node_index = np.argmin(distances)
return nearest_node_index
def is_collision_free(self, point):
for obstacle in self.obstacles:
if obstacle.contains_point(point):
return False
return True
def steer(self, start, end):
direction = end - start
norm = np.linalg.norm(direction)
if norm <= self.step_size:
return end
else:
return start + direction * (self.step_size / norm)
def generate_path(self):
self.nodes.append(self.start)
for _ in range(self.max_iter):
random_node = self.generate_random_node()
nearest_node_index = self.find_nearest_node(random_node)
nearest_node = self.nodes[nearest_node_index]
new_node = self.steer(nearest_node, random_node)
if not self.is_collision_free(new_node):
continue
self.nodes.append(new_node)
if np.linalg.norm(new_node - self.goal) < self.step_size:
self.nodes.append(self.goal)
break
if len(self.nodes) > 0 and np.linalg.norm(self.nodes[-1] - self.goal) >= self.step_size:
return None
return self.nodes
def plot(self):
plt.figure()
for obstacle in self.obstacles:
plt.plot(*obstacle.exterior.xy, 'r-')
if self.nodes is not None:
path = np.array(self.nodes)
plt.plot(path[:, 0], path[:, 1], 'b-')
plt.plot(self.start[0], self.start[1], 'go')
plt.plot(self.goal[0], self.goal[1], 'ro')
plt.xlim(*self.xlim)
plt.ylim(*self.ylim)
plt.gca().set_aspect('equal', adjustable='box')
plt.show()
```
该示例中的`RRT`类实现了RRT算法的基本逻辑。您可以通过设置起点,目标点,障碍物,以及环境的x和y边界来使用该算法。然后,通过调用`generate_path`方法生成路径。最后,通过调用`plot`方法可视化路径和环境。
请注意,该示例中的障碍物使用了`shapely`库来表示和检测碰撞。您可以根据自己的需求进行适当的修改和扩展。
希望这个示例对您有所帮助!