saberbud/PathPlanning
1
0
Fork 0
mirror of https://github.com/zhm-real/PathPlanning.git synced 2026-08-29 08:34:46 +08:00
Code Issues Packages Projects Releases Wiki Activity

update

Browse Source
This commit is contained in:
zhm-real
2020-06-20 19:52:56 -07:00
parent 45089174cb
commit a035aa5504
9 changed files with 24 additions and 52 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Model-free Control/Q-learning.py
+9 -12
View File
@@ -8,16 +8,13 @@ import env
import plotting
import motion_model
import matplotlib.pyplot as plt
import numpy as np
import sys
class QLEARNING:
def __init__(self, x_start, x_goal):
self.xI, self.xG = x_start, x_goal
self.M = 500 # iteration numbers
self.gamma = 0.9 # discount factor
self.M = 500 # iteration numbers
self.gamma = 0.9 # discount factor
self.alpha = 0.5
self.epsilon = 0.1
@@ -25,10 +22,10 @@ class QLEARNING:
self.motion = motion_model.Motion_model(self.xI, self.xG)
self.plotting = plotting.Plotting(self.xI, self.xG)
self.u_set = self.env.motions # feasible input set
self.stateSpace = self.env.stateSpace # state space
self.obs = self.env.obs_map() # position of obstacles
self.lose = self.env.lose_map() # position of lose states
self.u_set = self.env.motions # feasible input set
self.stateSpace = self.env.stateSpace # state space
self.obs = self.env.obs_map() # position of obstacles
self.lose = self.env.lose_map() # position of lose states
self.name1 = "SARSA, M=" + str(self.M)
@@ -49,10 +46,10 @@ class QLEARNING:
for k in range(self.M): # iterations
x = self.state_init() # initial state
while x != xG: # stop condition
while x != xG: # stop condition
u = self.epsilon_greedy(int(np.argmax(Q_table[x])), self.epsilon) # epsilon_greedy policy
x_next = self.move_next(x, self.u_set[u]) # next state
reward = self.env.get_reward(x_next) # reward observed
reward = self.env.get_reward(x_next) # reward observed
Q_table[x][u] = (1 - self.alpha) * Q_table[x][u] + \
self.alpha * (reward + self.gamma * max(Q_table[x_next]))
x = x_next
@@ -139,7 +136,7 @@ class QLEARNING:
"""
x, path = xI, [xI]
while x not in xG:
while x != xG:
u = self.u_set[policy[x]]
x_next = (x[0] + u[0], x[1] + u[1])
if x_next in self.obs:
Model-free Control/Sarsa.py
+11 -17
View File
@@ -10,12 +10,11 @@ import motion_model
import numpy as np
class SARSA:
def __init__(self, x_start, x_goal):
self.xI, self.xG = x_start, x_goal
self.M = 500 # iteration numbers
self.gamma = 0.9 # discount factor
self.M = 500 # iteration numbers
self.gamma = 0.9 # discount factor
self.alpha = 0.5
self.epsilon = 0.1
@@ -23,18 +22,17 @@ class SARSA:
self.motion = motion_model.Motion_model(self.xI, self.xG)
self.plotting = plotting.Plotting(self.xI, self.xG)
self.u_set = self.env.motions # feasible input set
self.stateSpace = self.env.stateSpace # state space
self.obs = self.env.obs_map() # position of obstacles
self.lose = self.env.lose_map() # position of lose states
self.u_set = self.env.motions # feasible input set
self.stateSpace = self.env.stateSpace # state space
self.obs = self.env.obs_map() # position of obstacles
self.lose = self.env.lose_map() # position of lose states
self.name1 = "SARSA, M=" + str(self.M)
self.name1 = "Q-learning, M=" + str(self.M)
[self.value, self.policy] = self.Monte_Carlo(self.xI, self.xG)
self.path = self.extract_path(self.xI, self.xG, self.policy)
self.plotting.animation(self.path, self.name1)
def Monte_Carlo(self, xI, xG):
"""
Monte_Carlo experiments
@@ -48,9 +46,9 @@ class SARSA:
for k in range(self.M): # iterations
x = self.state_init() # initial state
u = self.epsilon_greedy(int(np.argmax(Q_table[x])), self.epsilon)
while x != xG: # stop condition
while x != xG: # stop condition
x_next = self.move_next(x, self.u_set[u]) # next state
reward = self.env.get_reward(x_next) # reward observed
reward = self.env.get_reward(x_next) # reward observed
u_next = self.epsilon_greedy(int(np.argmax(Q_table[x_next])), self.epsilon)
Q_table[x][u] = (1 - self.alpha) * Q_table[x][u] + \
self.alpha * (reward + self.gamma * Q_table[x_next][u_next])
@@ -61,7 +59,6 @@ class SARSA:
return Q_table, policy
def table_init(self):
"""
Initialize Q_table: Q(s, a)
@@ -81,7 +78,6 @@ class SARSA:
Q_table[x] = u
return Q_table
def state_init(self):
"""
initialize a starting state
@@ -93,7 +89,6 @@ class SARSA:
if (i, j) not in self.obs:
return (i, j)
def epsilon_greedy(self, u, error):
"""
generate a policy using epsilon_greedy algorithm
@@ -114,7 +109,6 @@ class SARSA:
return u_e
return u
def move_next(self, x, u):
"""
get next state.
@@ -140,12 +134,12 @@ class SARSA:
"""
x, path = xI, [xI]
while x not in xG:
while x != xG:
u = self.u_set[policy[x]]
x_next = (x[0] + u[0], x[1] + u[1])
if x_next in self.obs:
print("Collision! Please run again!")
break
return path
else:
path.append(x_next)
x = x_next
Model-free Control/__pycache__/env.cpython-37.pyc
BIN
View File
Binary file not shown.
Model-free Control/__pycache__/motion_model.cpython-37.pyc
BIN
View File
Binary file not shown.
Model-free Control/__pycache__/plotting.cpython-37.pyc
BIN
View File
Binary file not shown.
Model-free Control/env.py
+3 -3
View File
@@ -6,7 +6,7 @@
class Env():
def __init__(self, xI, xG):
self.x_range = 14 # size of background
self.x_range = 14 # size of background
self.y_range = 6
self.motions = [(1, 0), (-1, 0), (0, 1), (0, -1)]
self.xI = xI
@@ -72,5 +72,5 @@ class Env():
"""
if x_next in self.lose:
return -100 # reward : -100, for lose states
return -1 # reward : -1, for other states
return -100 # reward : -100, for lose states
return -1 # reward : -1, for other states
Model-free Control/motion_model.py
-1
View File
@@ -11,7 +11,6 @@ class Motion_model():
self.env = env.Env(xI, xG)
self.obs = self.env.obs_map()
def move_next(self, x, u, eta=0.2):
"""
Motion model of robots,
Model-free Control/plotting.py
-6
View File
@@ -14,7 +14,6 @@ class Plotting():
self.obs = self.env.obs_map()
self.lose = self.env.lose_map()
def animation(self, path, name):
"""
animation.
@@ -29,7 +28,6 @@ class Plotting():
self.plot_lose()
self.plot_path(path)
def plot_grid(self, name):
"""
plot the obstacles in environment.
@@ -48,7 +46,6 @@ class Plotting():
plt.title(name)
plt.axis("equal")
def plot_lose(self):
"""
plot losing states in environment.
@@ -60,7 +57,6 @@ class Plotting():
plt.plot(lose_x, lose_y, color = '#A52A2A', marker = 's', ms = 24)
def plot_visited(self, visited):
"""
animation of order of visited nodes.
@@ -87,7 +83,6 @@ class Plotting():
if count % length == 0: plt.pause(0.001)
def plot_path(self, path):
path.remove(self.xI)
path.remove(self.xG)
@@ -100,7 +95,6 @@ class Plotting():
plt.show()
plt.pause(0.5)
def plot_diff(self, diff, name):
plt.figure(2)
plt.title(name, fontdict=None)
Search-based Planning/.idea/workspace.xml
Generated
+1 -13
View File
@@ -1,19 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ChangeListManager">
<list default="true" id="025aff36-a6aa-4945-ab7e-b2c625055f47" name="Default Changelist" comment="">
<change beforePath="$PROJECT_DIR$/../Model-free Control/Q-learning.py" beforeDir="false" afterPath="$PROJECT_DIR$/../Model-free Control/Q-learning.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/../Model-free Control/Sarsa.py" beforeDir="false" afterPath="$PROJECT_DIR$/../Model-free Control/Sarsa.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/../Model-free Control/env.py" beforeDir="false" afterPath="$PROJECT_DIR$/../Model-free Control/env.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/../Model-free Control/motion_model.py" beforeDir="false" afterPath="$PROJECT_DIR$/../Model-free Control/motion_model.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/../Model-free Control/tools.py" beforeDir="false" afterPath="$PROJECT_DIR$/../Model-free Control/plotting.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
<change beforePath="$PROJECT_DIR$/a_star.py" beforeDir="false" afterPath="$PROJECT_DIR$/a_star.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/bfs.py" beforeDir="false" afterPath="$PROJECT_DIR$/bfs.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/dfs.py" beforeDir="false" afterPath="$PROJECT_DIR$/dfs.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/dijkstra.py" beforeDir="false" afterPath="$PROJECT_DIR$/dijkstra.py" afterDir="false" />
<change beforePath="$PROJECT_DIR$/queue.py" beforeDir="false" afterPath="$PROJECT_DIR$/queue.py" afterDir="false" />
</list>
<list default="true" id="025aff36-a6aa-4945-ab7e-b2c625055f47" name="Default Changelist" comment="" />
<option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
<option name="SHOW_DIALOG" value="false" />
<option name="HIGHLIGHT_CONFLICTS" value="true" />