def run_dfs(map_path):
g = graph_search.GridMap(map_path)
res = graph_search.dfs(g.init_pos, g.transition, g.is_goal,
graph_search._ACTIONS)
print("Path: " + str(res[0]))
print("Visited: " + str(res[1]))
g.display_map(res[0], res[1])
def run_bfs(map_path):
g = graph_search.GridMap(map_path)
res = graph_search.bfs(g.init_pos, g.transition, g.is_goal,
graph_search._ACTIONS)
#res = graph_search.bfs(g.init_pos, g.transition, g.is_goal, graph_search._ACTIONS_2)
#actionset = res[0];
print("Plan: " + str(res[0]))
print("Visited: " + str(res[1]))
#print res;
#g.display_map(res[0],res[1])
y = len(res[0])
res1 = g.init_pos
list = []
for x in range(0, y):
i = 0
actionset = res[0][i]
i = +1
res1 = g.bfs_simulator(res1,
res[0][x],
graph_search._ACTIONS,
action_probability=0.8,
neighbour_probability=0.1,
ortho_probability=0,
simulate=False)
#res1 = g.bfs_simulator(res1, res[0][x], graph_search._ACTIONS_2, action_probability=0.8, neighbour_probability=0.1, ortho_probability=0.05, simulate=False)
#res1= graph_search.GridMap.bfs_simulator()
list.append(res1)
#print res1;
print(list)
g.display_map(list, res[1])
def run_astar(map_path):
g = graph_search.GridMap(map_path)
#res = graph_search.a_star_search(g.init_pos, g.transition, g.is_goal, graph_search._ACTIONS_2, g.uninformed_heuristic_euclidean)
res = graph_search.a_star_search(g.init_pos, g.transition, g.is_goal,
graph_search._ACTIONS_2,
g.uninformed_heuristic_manhattan)
print("Path: " + str(res[0]))
print("Visited: " + str(res[1]))
g.display_map(res[0], res[1])
def run_value_iteration(map_path):
start = time.time()
g = graph_search.GridMap(map_path)
actions_list = graph_search._ACTIONS
#actions_list1 = graph_search._ACTIONS_2
values = g.findValues(10, -1)
result = g.value_iteration(0.8, values, actions_list, 0.8, 0.1, 0)
#result = g.value_iteration(0.8, values, actions_list1, 0.8, 0.1, 0.0)
print("run time: " + str(time.time() - start))
print(result[0])
print(result[1])
g.display_values(result[0])
g.display_policy(result[0], result[1])
def run_PI(map_path):
start = time.time()
g = graph_search.GridMap(map_path)
actions_list = graph_search._ACTIONS
#actions_list1 = graph_search._ACTIONS_2
values = g.findValues(10, 0)
policy = g.find_policy(actionset=actions_list, randomize=True)
#policy = g.find_policy(actionset= actions_list1, randomize= True)
result = g.PI(0.8, values, actions_list, 0.8, 0.1, 0.0, policy)
#result = g.PI(0.8,values,actions_list1,0.8,0.1,0,policy)
print("run time: " + str(time.time() - start))
print(result[0])
print(result[1])
g.display_values(result[0])
g.display_policy(result[0], result[1])
import graph_search
g = graph_search.GridMap('./map0.txt')
file = open('output0.txt', 'a')
[[path, action_path],visited]=graph_search.dfs(g.init_pos , g.transition , g.is_goal, graph_search._ACTIONS)
file.write("BFS on map0: path = "+str(path) + "\n")
file.write("BFS on map0: action_path = "+str(action_path) + "\n")
file.write("BFS on map0: visited = "+str(visited) + "\n")
g.display_map(path,visited)
file.close()
import graph_search
g = graph_search.GridMap('./map1.txt')
file = open('output1.txt', 'a')
[[path, action_path],visited]=graph_search.dfs(g.init_pos , g.transition , g.is_goal, graph_search._ACTIONS)
file.write("BFS on map1: path = "+str(path) + "\n")
file.write("BFS on map1: action_path = "+str(action_path) + "\n")
file.write("BFS on map2: visited = "+str(visited) + "\n")
g.display_map(path,visited)
file.close()
import graph_search
g = graph_search.GridMap('./map2.txt')
file = open('output2.txt', 'a')
[[path, action_path],visited]=graph_search.dfs(g.init_pos , g.transition , g.is_goal, graph_search._ACTIONS)
file.write("BFS on map2: path = "+str(path) + "\n")
file.write("BFS on map2: action_path = "+str(action_path) + "\n")
file.write("BFS on map2: visited = "+str(visited) + "\n")
g.display_map(path,visited)
file.close()
s = sim.Sim()
s.sim_connect()
s.sim_start()
s.sim_get_handles()
#If using V_REP, start second thread for rover control
if not _SANS_V_REP:
#Start the interface thread to send frame instructions
try:
thread.start_new_thread( s.sim_drive_rover, ())
except:
print "Error: unable to start thread"
#Load terrain image file and compute slope map
print "Loading", cmn._map_file
g = graph_search.GridMap(s, cmn._map_file)
g.calcRatesOfChange(n=3, ret=False,dbg=False)
#Create plotes for each action direction and save to disk
cmap = cm.Spectral;
cmap.set_bad(color='k')
cmn.createArrImg(g.height_map, cmap=cmap, plotTitle='Height Map', fn=os.path.join(cmn._IMG_FLDR, 'heightmap.svg'),
show=False)
for a in cmn._actions:
cmn.createArrImg(g.rates[0][a], cmap=cmap, plotTitle='Rate Map: {}'.format(a),
fn=os.path.join(cmn._IMG_FLDR, 'ratemap_{}.svg'.format(a)), show=False)
cmn.overlayArrImgs(arr1=g.height_map, arr2=g.rates[0][a], plotTitle='Overlayed Rate Map: {}'.format(a),
fn=os.path.join(cmn._IMG_FLDR, 'ratemap_ovr_{}.svg'.format(a)), show=False)
rover_pos = s.sim_get_xy(s.rover_handle)
changed_rover_pos = cmn.convert_VREPXY(rover_pos)
def run_dfs(map_path):
g = graph_search.GridMap(map_path)
res = graph_search.dfs(g.init_pos, g.transition, g.is_goal,
graph_search._ACTIONS)
g.display_map(res[0][0], res[1])