#!/usr/bin/python
#?_*_?coding:?UTF-8?_*_
import?matplotlib.pyplot?as?plt
import?random
import?math
import?copy
from?scipy?import?optimize
show_animation?=?True
import?numpy?as?np

class?Node（object）:
????“““
????RRT?Node
????“““

????def?__init__（self?x?y）:
????????self.x?=?x
????????self.y?=?y
????????self.parent?=?None


class?RRT（object）:
????“““
????Class?for?RRT?Planning
????“““

????def?__init__（self?start?near_points?far_points?obstacle_list?rand_area）:
????????“““
????????Setting?Parameter

????????start:Start?Position?[xy]
????????goal:Goal?Position?[xy]
????????obstacleList:obstacle?Positions?[[xysize]...]
????????randArea:random?sampling?Area?[minmax]

????????“““
????????self.start_Ta?=?Node（start[0]?start[1]）
????????self.end?=?Node（near_points[0]?near_points[1]）

????????self.start_Tb?=?Node（far_points[0]?far_points[1]）


????????self.min_rand_x?=?rand_area[0]
????????self.max_rand_x?=?rand_area[1]
????????self.min_rand_y?=?rand_area[2]
????????self.max_rand_y?=?rand_area[3]????????
????????self.expandDis?=?1.0
????????self.goalSampleRate?=?0.05??#?選擇終點的概率是0.05
????????self.maxIter?=?500
????????self.obstacleList?=?obstacle_list
????????self.nodeList?=?[]


????def?random_node（self?mean?cov）:
????????“““
????????產生隨機節點
????????start?point----->?near?points
????????Far?point?------>?near?points
????????:return:
????????“““

????????node_x?node_y??=?np.random.multivariate_normal（mean?cov?1）.T
????????node?=?[node_x?node_y]

????????return?node

????@staticmethod
????def?get_nearest_list_index（node_list?rnd）:
????????“““
????????:param?node_list:
????????:param?rnd:
????????:return:
????????“““

????????d_list?=?[math.sqrt（（node.x?-?rnd[0]）?**?2?+?（node.y?-?rnd[1]）?**?2）?for?node?in?node_list]
????????‘‘‘
????????theta_list?=?[abs（math.atan（（node.y?-?rnd[1]）/（node.x?-?rnd[0]）））?for?node?in?node_list]
????????

????????w_dis?=?0.5
????????w_theta?=?0.5

????????theta_list_normlize?=?[w_theta*（math.pi-theta）/math.pi?for?theta?in?theta_list]
????????d_list_normlize?=?[w_dis*（20-distance）/20?for?distance?in?d_list]

????????metric_list?=?np.array（d_list_normlize）?+?np.array（theta_list_normlize）
????????metric_list?=?metric_list.tolist（）
????????‘‘‘
????????
????????min_index?=?d_list.index（min（d_list））
????????return?min_index

????@staticmethod
????def?collision_check（new_node?obstacle_list）:
????????a?=?1
????????for?（ox?oy?size）?in?obstacle_list:
????????????dx?=?ox?-?new_node.x
????????????dy?=?oy?-?new_node.y
????????????d?=?math.sqrt（dx?*?dx?+?dy?*?dy）
????????????if?d?<=?size:
????????????????a?=?0??#?collision

????????return?a??#?safe


????def?planning（self?flag）:
????????“““
????????Path?planning

????????animation:?flag?for?animation?on?or?off
????????“““
????????if?flag?==?0:
????????????start?=?self.start_Ta
????????????mean?=?[510]
????????????cov?=?[[10][01]]

????????else:
????????????#far_dictribution
????????????start?=?self.start_Tb
????????????mean?=?[205]
????????????cov?=?[[200][01