def __init__(self, map_path="maps/map1.txt",
search_algorithm=SearchAlgorithm.DFS):
self.__occupancy_map = OccupancyMap(map_path)
self.__search_algorithm = search_algorithm
self.__start_pos = self.__occupancy_map.get_start_pos()
pass
class Robot(object):
def __init__(self, map_path="maps/map1.txt",
search_algorithm=SearchAlgorithm.DFS):
self.__occupancy_map = OccupancyMap(map_path)
self.__search_algorithm = search_algorithm
self.__start_pos = self.__occupancy_map.get_start_pos()
pass
def set_search_algorithm(self, search_algorithm=SearchAlgorithm.DFS):
self.__search_algorithm = search_algorithm
pass
def set_map(self, occupancy_map):
self.__occupancy_map = occupancy_map
def start_cleaning(self):
if self.__search_algorithm == SearchAlgorithm.DFS:
print "Starting a DFS search..."
dirty_tiles = self.__perform_algorithm()
elif self.__search_algorithm == SearchAlgorithm.BFS:
print "Starting a BFS search..."
dirty_tiles = self.__perform_algorithm()
else:
print "Starting a uniform cost search..."
dirty_tiles = self.__perform_algorithm()
print "... found dirty tiles at:", dirty_tiles
pass
def __clean_tile(self, node):
self.__occupancy_map.set_tile(tuple(node.indizes), MapState.CLEAN)
node.dirty = False
pass
def __expand(self, node):
directions = np.array([[-1, 0], [1, 0], [0, -1], [0, 1]])
new_nodes = []
for direction in directions:
new_indizes = tuple(node.indizes + direction)
if self.__occupancy_map.get_tile(new_indizes) != MapState.BLOCKED:
new_node = Node(new_indizes,
self.__occupancy_map.get_tile(new_indizes),
[node])
new_nodes.append(new_node)
pass
return new_nodes
pass
def __perform_algorithm(self):
# Discovered nodes
discovered = []
# Found dirty nodes
dirty_tiles = []
# The start node
start_node = Node(self.__start_pos,
self.__occupancy_map.get_tile(self.__start_pos),
[])
# Start with the start_node
queue = [start_node]
# While the queue is not empty there is undiscovered space
while queue:
# Get the next node to expand, depending on the algorithm
if (self.__search_algorithm == SearchAlgorithm.BFS
or self.__search_algorithm == SearchAlgorithm.UNIFORM):
current_node = queue.pop(0)
elif self.__search_algorithm == SearchAlgorithm.DFS:
current_node = queue.pop()
# If the node is dirty, save and clean it
if (self.__occupancy_map.get_tile(current_node.indizes)
== MapState.DIRTY):
dirty_tiles.append(current_node)
self.__clean_tile(current_node)
# If the node wasn't already discovered, expand it
if current_node not in discovered:
discovered.append(current_node)
if (self.__occupancy_map.get_tile(current_node.indizes)
!= MapState.DIRTY):
self.__occupancy_map.set_tile(current_node.indizes,
MapState.VISITED)
#self.__occupancy_map.draw_map()
new_nodes = self.__expand(current_node)
# If nodes were created with the expansion, enqueue them
if new_nodes:
# BFS appends all expanded nodes to the queue
if (self.__search_algorithm == SearchAlgorithm.BFS
or self.__search_algorithm == SearchAlgorithm.DFS):
queue += new_nodes
# Uniform Search checks if the node already exists.
# If it has lower costs, replace the costs
elif self.__search_algorithm == SearchAlgorithm.UNIFORM:
# Do the following for each expanded node
for new_node in new_nodes:
# If the node is not in the queue yet,
# add it and resume.
if not new_node in queue:
queue.append(new_node)
else:
# Calculate the new costs
new_node.costs = current_node.costs + 1
# Check if the existing node has higher costs
for node in queue:
# If so, replace the costs
if new_node.costs < node.costs:
queue.remove(node)
queue.append(new_node)
# After the queue is empty, return all found dirty tiles
return dirty_tiles
pass
pass
