RRT实现机械臂避障代码

RRT（Rapidly-exploring Random Tree）是一种常用的路径规划算法，用于解决机械臂避障问题。下面是一个简单的RRT实现机械臂避障的代码示例：

import numpy as np

class Node:
    def __init__(self, q):
        self.q = q
        self.parent = None

class RRT:
    def __init__(self, start, goal, obstacles, step_size, max_iter):
        self.start = Node(start)
        self.goal = Node(goal)
        self.obstacles = obstacles
        self.step_size = step_size
        self.max_iter = max_iter
        self.nodes = []

    def generate_random_node(self):
        q_rand = np.random.uniform(low=-np.pi, high=np.pi, size=len(self.start.q))
        return Node(q_rand)

    def find_nearest_node(self, q_rand):
        distances = [self.distance(q_rand, node.q) for node in self.nodes]
        nearest_node = self.nodes[np.argmin(distances)]
        return nearest_node

    def extend(self, q_near, q_rand):
        q_new = q_near.q + self.step_size * (q_rand.q - q_near.q) / np.linalg.norm(q_rand.q - q_near.q)
        if not self.collision_check(q_new):
            q_new_node = Node(q_new)
            q_new_node.parent = q_near
            self.nodes.append(q_new_node)
            return q_new_node
        return None

    def plan(self):
        self.nodes.append(self.start)
        for _ in range(self.max_iter):
            q_rand = self.generate_random_node()
            q_near = self.find_nearest_node(q_rand)
            q_new = self.extend(q_near, q_rand)
            if q_new and self.distance(q_new.q, self.goal.q) < self.step_size:
                self.goal.parent = q_new
                return self.generate_path()
        return None

    def generate_path(self):
        path = []
        node = self.goal
        while node:
            path.append(node.q)
            node = node.parent
        return path[::-1]

    def distance(self, q1, q2):
        return np.linalg.norm(q1 - q2)

    def collision_check(self, q):
        for obstacle in self.obstacles:
            if self.distance(q, obstacle) < 0.5:  # 假设机械臂的碰撞半径为0.5
                return True
        return False

# 示例使用
start = np.array([0, 0, 0])
goal = np.array([np.pi/2, np.pi/2, np.pi/2])
obstacles = [np.array([1, 1, 1]), np.array([-1, -1, -1])]
step_size = 0.1
max_iter = 1000

rrt = RRT(start, goal, obstacles, step_size, max_iter)
path = rrt.plan()
if path:
    print("找到路径：")
    for q in path:
        print(q)
else:
    print("未找到路径")

这段代码实现了一个简单的RRT算法，用于机械臂的避障路径规划。其中，`start`表示起始位置，`goal`表示目标位置，`obstacles`表示障碍物的位置，`step_size`表示每次扩展的步长，`max_iter`表示最大迭代次数。代码中的`collision_check`函数用于检测机械臂是否与障碍物发生碰撞，可以根据实际情况进行修改。