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bit_star.py
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#Author: Nicholas Massad
#Date: 28/02/2023
from rrt import InformedRRTStar2D
from node import Node
from queue import PriorityQueue
from collisionManager import CollisionManager2D
import numpy as np
from fmt import FMTStar2D
import time
import math
import random
def calculate_distance(node1, node2):
return ((node1.pos[0] - node2.pos[0]) ** 2 + (node1.pos[1] - node2.pos[1]) ** 2) ** 0.5
class BitStar(InformedRRTStar2D, FMTStar2D):
def __init__(self, environement, game_engine, radius_multiplier=1.8, dimension=2, free_space_volume=None, K = 200, benchmark=False):
super().__init__(environement, game_engine, benchmark=benchmark)
self.K = K
self.radius_multiplier = radius_multiplier
if not benchmark:
self.game_engine = game_engine
else:
self.game_engine = None
self.environement = environement
self.dimension = dimension
self.collision_manager = CollisionManager2D(game_engine.obstacles, self.environement)
if free_space_volume is None:
self.free_space_volume = (environement['width'] - 2 * environement['grid_size']) * (
environement['height'] - 2 * environement['grid_size']) - len(self.collision_manager.obstacles) * \
environement['grid_size'] ** 2
else:
self.free_space_volume = free_space_volume
self.ellipsoid_params = None
self.start_node = None
self.end_node = None
self.c_best = None
# TODO: fix the bug with the block in front of the start
def find_path(self, start_pos, end_pos, progress=False, optimise_time=None):
safety_time = time.time()
unvisited_set = self.sampleFree(self.K)
open_set = PriorityQueue()
closed_set = set()
self.start_node = Node(None, start_pos)
self.end_node = Node(None, end_pos)
self.c_best = calculate_distance(self.start_node, self.end_node)+10
self.ellipsoid_params = self.calculate_elipsoid_params_homebrew(self.start_node, self.end_node, self.c_best)
open_set.put((0, self.start_node))
unvisited_set[self.end_node.pos] = self.end_node
radius = self.calculate_radius(self.K)
unvisited_set = self.assureGoalState(unvisited_set, self.end_node, radius)
current_node = self.start_node
start = True
Found_path = False
if optimise_time is None:
stop_safety = 5
else:
stop_safety = optimise_time+1
while current_node is not self.end_node and time.time() - safety_time < stop_safety:
self.expand_tree(current_node, open_set, unvisited_set, radius, progress)
closed_set.add(current_node)
if start:
remove_start = open_set.get()[1]
start = False
if open_set.empty() and not Found_path:
self.moveClosedSetToOpenSet(open_set, closed_set)
self.c_best += 10
self.ellipsoid_params = self.calculate_elipsoid_params_homebrew(self.start_node, self.end_node, self.c_best)
current_node = open_set.get()[1]
if current_node == self.end_node:
Found_path = True
if optimise_time is not None:
return self.optimise_path(current_node, time.time(), optimise_time, radius, progress, graph=closed_set)
return self.reconstruct_path(self.end_node)
return None
def create_node(self, elipsoid_params=None):
node = None
if elipsoid_params is not None:
while node is None:
center = elipsoid_params['center']
a = elipsoid_params['c_best']/2
b = elipsoid_params['b']/2
d = random.random()
theta = random.random()*2*math.pi
r = (a * b)/math.sqrt((a * math.sin(theta))**2 + (b * math.cos(theta))**2)
pos = (r*d*math.cos(theta)+center[0], r*d*math.sin(theta)+center[1])
pos = self.rotate_vector((pos[0]-center[0], pos[1]-center[1]), elipsoid_params['angle'])
pos = (pos[0]+center[0], pos[1]+center[1])
if self.environement['width'] > pos[0] > self.environement['grid_size'] and self.environement['height'] > pos[1] > self.environement['grid_size']:
if self.collision_manager.collision_check(pos):
node = Node(position=tuple(pos))
return node
while node is None:
point = self.generate_random_point()
if self.collision_manager.collision_check(point):
node = Node(position=tuple(point))
return node
def sampleFree(self, n, ellipsoid_params=None):
sampleSpace = {}
for i in range(n):
node = self.create_node(ellipsoid_params)
sampleSpace[node.pos] = node
return sampleSpace
def moveClosedSetToOpenSet(self, open_set, closed_set):
for node in closed_set:
open_set.put((node.cost, node))
closed_set.clear()
def near(self, node, samples, radius):
if self.ellipsoid_params is not None:
in_range = [n for n in samples if calculate_distance(n, node) < radius and n != node]
return [n for n in in_range if self.inEllipse(n, self.ellipsoid_params)]
else:
return [n for n in samples if calculate_distance(n, node) < radius and n != node]
def expand_tree(self, x, open, unvisited, radius, progress, start_time=None):
nearX = self.near(x, unvisited.values(), radius)
if len(nearX) > 0:
for y in nearX:
if y is not x.parent:
nearY = self.near(y, list(dict(open.queue).values()), radius)
if len(nearY) > 0:
ymin = np.argmin(calculate_distance(y, z) + z.cost for z in nearY)
if self.collision_manager.collision_check(nearY[ymin].pos, y.pos):
y.parent = nearY[ymin]
y.cost = nearY[ymin].cost + calculate_distance(y, nearY[ymin])
open.put((y.cost, y))
del unvisited[y.pos]
if self.game_engine is not None:
if progress:
if start_time is not None:
temp_start_time = time.time()
self.game_engine.add_path(y.pos[0], y.pos[1], y.parent.pos[0], y.parent.pos[1], rgb=(148, 0, 211))
temp_stop_time = time.time()
start_time += temp_stop_time - temp_start_time
else:
self.game_engine.add_path(y.pos[0], y.pos[1], y.parent.pos[0], y.parent.pos[1], rgb=(148, 0, 211))
def optimise_path(self, current_node, time_start, time_optimise, radius=None, progress=False, graph=None):
path_list = PriorityQueue()
open_set = PriorityQueue()
closed_set = graph
unvisited_set = {}
c_best_init = current_node.cost # current node is the end node
path = self.reconstruct_path(current_node)
self.c_best = self.end_node.cost
path_list.put((self.c_best, path))
while time.time() - time_start < time_optimise:
self.ellipsoid_params = self.calculate_elipsoid_params_homebrew(self.start_node, self.end_node, self.c_best)
unvisited_set = self.sampleFree(self.K, self.ellipsoid_params)
self.prune(open_set, closed_set, unvisited_set, self.ellipsoid_params)
unvisited_set[self.end_node.pos] = self.end_node
radius = self.calculate_radius(self.K)
unvisited_set = self.assureGoalState(unvisited_set, self.end_node, radius)
current_node = self.start_node
start = True
while current_node is not self.end_node:
self.expand_tree(current_node, open_set, unvisited_set, radius, progress, time_start)
closed_set.add(current_node)
if open_set.empty():
break
if start:
remove_start = open_set.get()[1]
start = False
current_node = open_set.get()[1]
if current_node == self.end_node:
path = self.reconstruct_path(self.end_node)
if path is not None:
self.c_best = self.end_node.cost
path_list.put((self.c_best, path))
(self.c_best, path) = path_list.get()
print("Initial cost: ", c_best_init)
print("Optimised cost: ", self.c_best)
return path
def prune(self, open_set, closed_set, unvisited_set, ellipsoid_params):
for node in closed_set:
if not self.inEllipse(node, ellipsoid_params):
unvisited_set[node.pos] = node
open_set.put((0, self.start_node))
closed_set.clear()