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main.py
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main.py
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import numpy as np
import turtle
import argparse
import time
import matplotlib.pyplot as plt
from maze import Maze, Particle, Robot, WeightedDistribution, weight_gaussian_kernel
plt.rcParams['font.sans-serif']=['Songti SC'] # 用来正常显示中文标签
def main(window_width, window_height, num_particles, sensor_limit_ratio, grid_height, grid_width, num_rows, num_cols, wall_prob, random_seed, robot_speed, kernel_sigma, particle_show_frequency):
sensor_limit = sensor_limit_ratio * max(grid_height * num_rows, grid_width * num_cols)
window = turtle.Screen()
window.setup (width = window_width, height = window_height)
world = Maze(grid_height = grid_height, grid_width = grid_width, num_rows = num_rows, num_cols = num_cols, wall_prob = wall_prob, random_seed = random_seed)
x = np.random.uniform(0, world.width)
y = np.random.uniform(0, world.height)
bob = Robot(x = x, y = y, maze = world, speed = robot_speed, sensor_limit = sensor_limit)
particles = list()
for i in range(num_particles):
x = np.random.uniform(0, world.width)
y = np.random.uniform(0, world.height)
particles.append(Particle(x = x, y = y, maze = world, sensor_limit = sensor_limit))
time.sleep(1)
world.show_maze()
# 保存位置信息
real_positions = []
estimated_positions = []
# distances = []
# plt.ion()
# fig, ax = plt.subplots()
# line, = ax.plot(distances, label='距离')
# plt.xlim([0, 100])
# plt.legend()
# plt.show()
while True:
# # 保存位置信息
real_positions.append((bob.x, bob.y))
estimated_positions.append((np.mean([particle.x for particle in particles]), np.mean([particle.y for particle in particles])))
# distance = np.sqrt((bob.x - np.mean([particle.x for particle in particles]))**2 + (bob.y - np.mean([particle.y for particle in particles]))**2)
# distances.append(distance)
# 更新图形
# line.set_ydata(distances) # 更新y轴的数据
# line.set_xdata(range(len(distances))) # 更新x轴的数据
# ax.relim() # 重新计算坐标轴的限制
# ax.autoscale_view() # 自动调整坐标轴的范围
# plt.draw() # 更新figure
# plt.pause(0.01) # 暂停一会，让GUI有机会更新figure
# print(distance)
readings_robot = bob.read_sensor(maze = world)
particle_weight_total = 0
for particle in particles:
readings_particle = particle.read_sensor(maze = world)
particle.weight = weight_gaussian_kernel(x1 = readings_robot, x2 = readings_particle, std = kernel_sigma)
particle_weight_total += particle.weight
world.show_particles(particles = particles, show_frequency = particle_show_frequency)
world.show_robot(robot = bob)
world.show_estimated_location(particles = particles)
world.show_track(positions=real_positions, color='blue') # 绘制轨迹
world.show_track(positions=estimated_positions, color='red') # 绘制轨迹
# world.clear_objects()
# 不能让粒子的权重全为0
if particle_weight_total == 0:
particle_weight_total = 1e-8
# 标准化权重
for particle in particles:
particle.weight /= particle_weight_total
# 重采样
distribution = WeightedDistribution(particles = particles)
particles_new = list()
for i in range(num_particles):
particle = distribution.random_select()
if particle is None:
x = np.random.uniform(0, world.width)
y = np.random.uniform(0, world.height)
particles_new.append(Particle(x = x, y = y, maze = world, sensor_limit = sensor_limit))
else:
particles_new.append(Particle(x = particle.x, y = particle.y, maze = world, heading = particle.heading, sensor_limit = sensor_limit, noisy = True))
particles = particles_new
heading_old = bob.heading
bob.move(maze = world)
heading_new = bob.heading
dh = heading_new - heading_old
for particle in particles:
particle.heading = (particle.heading + dh) % 360
particle.try_move(maze = world, speed = bob.speed)
if __name__ == '__main__':
window_width = 500 # 窗口宽度
window_height = 500 # 窗口高度
num_particles = 500 # 粒子数量
sensor_limit_ratio = 0.3 # 传感器范围
grid_height = 100 # 格子高度
grid_width = 100 # 格子宽度
num_rows = 25 # 行数
num_cols = 25 # 列数
wall_prob = 0.25 # 墙的概率
random_seed = 200 # 随机种子
robot_speed = 50 # 机器人速度
kernel_sigma = 80 # 核函数标准差
particle_show_frequency = 10 # 粒子显示频率
main(window_width = window_width, window_height = window_height, num_particles = num_particles, sensor_limit_ratio = sensor_limit_ratio, grid_height = grid_height, grid_width = grid_width, num_rows = num_rows, num_cols = num_cols, wall_prob = wall_prob, random_seed = random_seed, robot_speed = robot_speed, kernel_sigma = kernel_sigma, particle_show_frequency = particle_show_frequency)