def callback(data):
msg = target_positions_msg()
msg2 = strategy_output_msg()
msg.x[0] = 2
msg2.x[0] = 3
msg2.control_options[0] = control_options.position
pub.publish(msg)
pub2.publish(msg2)
def callback(data):
msg = target_positions_msg()
#Creating attractive potential
attract_ball = pf.AttractivePotentialField(
np.array([data.ball_x, data.ball_y]),
BALL_ATTRACTIVE, min_magnitude=0.3)
for robot in range(number_of_robots):
resultant_vector = attract_ball.calculate_force(np.array([data.x[robot], data.y[robot]]))
msg.x[robot] = resultant_vector[0]
msg.y[robot] = resultant_vector[1]
pub.publish(msg)
def measurement_callback(data):
msg = target_positions_msg()
ball = [data.ball_x, data.ball_y]
allies = [[], [], []]
for robot in range(3):
allies[robot] = [data.x[robot], data.y[robot]]
player.setPositions(allies=allies, ball=ball, field_side=field_side)
for i in range(3):
msg.x[i], msg.y[i] = player.getTarget()
pub.publish(msg)
def callback(data):
msg = target_positions_msg()
msg2 = strategy_output_msg()
ball = [data.ball_x, data.ball_y]
for robot in range(number_of_robots):
msg.x[robot] = data.ball_x
msg.y[robot] = data.ball_y
msg2.x[robot] = data.ball_x
msg2.y[robot] = data.ball_y
msg2.control_options[robot] = control_options.position
pub.publish(msg)
pub2.publish(msg2)
def convertTargetPositions(global_target):
msg = target_positions_msg()
for robot in range(number_of_robots):
relative_target = [
global_target.x[robot] - allies_x[robot],
global_target.y[robot] - allies_y[robot]
]
relative_target = convert_axis_to_robot(relative_target,
allies_th[robot])
msg.x[robot] = relative_target[0]
msg.y[robot] = relative_target[1]
pub.publish(msg)
def callback(data):
msg = target_positions_msg()
#PCreating an tangential field
tangencial_ball = pf.TangencialPotentialField(
np.array([data.ball_x, data.ball_y]), TANGENCIAL_BALL_MAGNITUDE)
for robot in range(number_of_robots):
resultant_vector = tangencial_ball.calculate_force(
np.array([data.x[robot], data.y[robot]]))
msg.x[robot] = resultant_vector[0]
msg.y[robot] = resultant_vector[1]
pub.publish(msg)
def callback(data):
msg = target_positions_msg()
ball = [data.ball_x, data.ball_y]
for i in range(3):
allies[i] = [data.x[i], data.y[i], data.th[i]]
for robot in range(number_of_robots):
player.setPositions(ball=ball, allies=allies, my_index=robot)
target = player.getTarget()
msg.x[robot] = target[0]
msg.y[robot] = target[1]
pub.publish(msg)
def callback(data):
msg = target_positions_msg()
#Potential Fields
attract_ball = pf.AttractivePotentialField(np.array(
[data.ball_x, data.ball_y]),
BALL_ATTRACTIVE,
min_magnitude=0.3)
kick_attract_ball = pf.AttractivePotentialField(
np.array([data.ball_x, data.ball_y]), BALL_ATTRACTIVE * 2)
tangencial_ball = pf.TangencialPotentialField(
np.array([data.ball_x, data.ball_y]), TANGENCIAL_BALL_MAGNITUDE)
repulsive_enemy_fields = generate_repulsive_field(data,
ENEMY_REPULSIVE_RANGE,
ENEMY_REPULSIVE_WEIGHT,
ally=False)
repulsive_ally_fields = generate_repulsive_field(data,
ALLY_REPULSIVE_RANGE,
ALLY_REPULSIVE_WEIGHT)
for robot in range(number_of_robots):
resultant_vector = np.array([0.0, 0.0])
#Calculate repulsive force from each enemy
for field in repulsive_enemy_fields:
resultant_vector += field.calculate_force(
np.array([data.x[robot], data.y[robot]]))
#Calculate repulsive force from each ally
for i in range(len(repulsive_ally_fields)):
#Ignore his own field
if i != robot:
resultant_vector += repulsive_ally_fields[i].calculate_force(
np.array([data.x[robot], data.y[robot]]))
#resultant_vector += tangencial_ball.calculate_force(np.array([data.x[robot], data.y[robot]]))
resultant_vector += attract_ball.calculate_force(
np.array([data.x[robot], data.y[robot]]))
msg.x[robot] = resultant_vector[0]
msg.y[robot] = resultant_vector[1]
pub.publish(msg)
def callback(data):
msg = target_positions_msg()
if (side_opponent == 'Right'):
opponent_goal = np.array([0.8, 0])
else:
opponent_goal = np.array([-0.8, 0])
direction = np.array([data.ball_x, data.ball_y]) - opponent_goal
#Creating attractive potential
selective_field = pf.SelectivePotentialField(
np.array([data.ball_x, data.ball_y]), SELECTIVE_WIDTH, SELECTIVE_RANGE,
direction, opponent_goal, 4, 0.3)
for robot in range(number_of_robots):
resultant_vector = selective_field.calculate_force(
np.array([data.x[robot], data.y[robot]]))
msg.x[robot] = resultant_vector[0]
msg.y[robot] = resultant_vector[1]
pub.publish(msg)
def callback(data):
msg = target_positions_msg()
obt_circle(msg)
pub.publish(msg)
def callback(data):
global k
msg = target_positions_msg()
set_3_pnts(msg)
pub.publish(msg)
