mirror of
https://github.com/zhm-real/PathPlanning.git
synced 2026-08-29 16:40:46 +08:00
zhm-real
93 lines
3.0 KiB
Python
93 lines
3.0 KiB
Python
import queue
|
|
import env
|
|
import plotting
|
|
|
|
|
|
class Dijkstra:
|
|
def __init__(self, x_start, x_goal):
|
|
self.xI, self.xG = x_start, x_goal
|
|
|
|
self.Env = env.Env()
|
|
self.plotting = plotting.Plotting(self.xI, self.xG)
|
|
|
|
self.u_set = self.Env.motions # feasible input set
|
|
self.obs = self.Env.obs # position of obstacles
|
|
|
|
[self.path, self.policy, self.visited] = self.searching(self.xI, self.xG)
|
|
|
|
self.fig_name = "Dijkstra's Algorithm"
|
|
self.plotting.animation(self.path, self.visited, self.fig_name) # animation generate
|
|
|
|
def searching(self, xI, xG):
|
|
"""
|
|
Searching using Dijkstra.
|
|
|
|
:return: planning path, action in each node, visited nodes in the planning process
|
|
"""
|
|
|
|
q_dijk = queue.QueuePrior() # priority queue
|
|
q_dijk.put(xI, 0)
|
|
parent = {xI: xI} # record parents of nodes
|
|
action = {xI: (0, 0)} # record actions of nodes
|
|
visited = [] # record visited nodes
|
|
cost = {xI: 0}
|
|
|
|
while not q_dijk.empty():
|
|
x_current = q_dijk.get()
|
|
if x_current == xG: # stop condition
|
|
break
|
|
visited.append(x_current)
|
|
for u_next in self.u_set: # explore neighborhoods of current node
|
|
x_next = tuple([x_current[i] + u_next[i] for i in range(len(x_current))])
|
|
if x_next not in self.obs: # node not visited and not in obstacles
|
|
new_cost = cost[x_current] + self.get_cost(x_current, u_next)
|
|
if x_next not in cost or new_cost < cost[x_next]:
|
|
cost[x_next] = new_cost
|
|
priority = new_cost
|
|
q_dijk.put(x_next, priority) # put node into queue using cost to come as priority
|
|
parent[x_next], action[x_next] = x_current, u_next
|
|
|
|
[path, policy] = self.extract_path(xI, xG, parent, action)
|
|
|
|
return path, policy, visited
|
|
|
|
def get_cost(self, x, u):
|
|
"""
|
|
Calculate cost for this motion
|
|
|
|
:param x: current node
|
|
:param u: input
|
|
:return: cost for this motion
|
|
:note: cost function could be more complicate!
|
|
"""
|
|
|
|
return 1
|
|
|
|
def extract_path(self, xI, xG, parent, policy):
|
|
"""
|
|
Extract the path based on the relationship of nodes.
|
|
|
|
:param xI: Starting node
|
|
:param xG: Goal node
|
|
:param parent: Relationship between nodes
|
|
:param policy: Action needed for transfer between two nodes
|
|
:return: The planning path
|
|
"""
|
|
|
|
path_back = [xG]
|
|
acts_back = [policy[xG]]
|
|
x_current = xG
|
|
while True:
|
|
x_current = parent[x_current]
|
|
path_back.append(x_current)
|
|
acts_back.append(policy[x_current])
|
|
if x_current == xI: break
|
|
|
|
return list(path_back), list(acts_back)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
x_Start = (5, 5) # Starting node
|
|
x_Goal = (49, 5) # Goal node
|
|
dijkstra = Dijkstra(x_Start, x_Goal)
|