self.path_list.append(self.smoothed_path)
if verbose:
t2 = time.time()
print('Generate multiple paths: {}\n'.format(t2 - t1))
if __name__ == '__main__':
# --- world class
world = World()
world.generate_frame([-pi, pi], [-pi, pi])
# --- Set start/goal point
world.start = np.array([-3.0, -3.0])
world.goal = np.array([3.0, 3.0])
# --- Set objects
og = ObjectGenerator(world)
og.generate_object_sample1()
og.set_object_type()
# '''
# --- Generate 10x10 valid roadmaps
t0 = time.time()
prm_list = [PRM(world, 100, 5) for i in range(10)]
path_list = []
for prm in prm_list:
prm.single_query(verbose=True)
if prm.path_list != []:
prm.multi_query(10, verbose=True)
# Objects in the cartesian space
og = ObjectGenerator(world)
og.generate_object([[3.5, 6.5], [3.5, 3.5], [6.5, 3.5], [6.5, 6.5]])
# Robot
robot2R = RobotArm(base=[0, 0], lengths=[3.0, 5.0])
robot2R.start = np.array([pi / 2, -pi / 7])
robot2R.goal = np.array([pi / 5, -pi / 7])
# C-space
cspace = World()
cspace.robot = robot2R
cspace.generate_frame([-pi, pi], [-pi, pi])
cspace.start = cspace.robot.start
cspace.goal = cspace.robot.goal
cspace.generate_cspace_objects([100, 100], world.objects)
cspace.generate_cspace_objects([100, 100], [world.frame])
cspace.type = 'cspace'
# world.start = np.array([-3.0, -3.0])
# world.goal = np.array([3.0, 3.0])
# og = ObjectGenerator(world)
# og.generate_object_sample1()
ga = GeneticAlgorithm(world=cspace,
NGEN=100,
n_ind=100,
n_elite=10,
fitness_thresh=0.0,
margin_on=False,
verbose=True)
'''
# --- world class
world = World()
# --- Set frame
world.frame = np.array(
[[-pi, -pi],
[-pi, pi],
[pi, pi],
[pi, -pi],
[-pi, -pi]])
# --- Set start/goal point
world.start = np.array([-pi / 2, -pi / 2]) * 1.9
world.goal = np.array([pi / 2, pi / 2]) * 1.9
# --- Generate objects
og = ObjectGenerator(world)
world.objects = og.example()
# og.generate(10, 5)
# og.locate([2.0, 3.0])
# world.objects = og.world.objects
# --- Generte Collision Checker
cc = CollisionChecker(world, 0.1)
'''
Functions
'''