def should_defending(self):
ball = self.info.ball
car = self.info.my_car
our_goal = self.info.my_goal.center
car_to_ball = ball.pos - car.pos
in_front_of_ball = distance_2d(ball.pos, our_goal) < distance_2d(
car.pos, our_goal)
backline_intersect = line_backline_intersect(
self.info.my_goal.center[1], vec2(car.pos), vec2(car_to_ball))
return in_front_of_ball and abs(backline_intersect) < 2000
def should_dodge(agent):
car = agent.info.my_car
their_goal = agent.info.their_goal
close_to_goal = distance_2d(car.pos, their_goal.center) < 4000
aiming_for_goal = abs(
line_backline_intersect(their_goal.center[1], vec2(car.pos),
vec2(car.forward()))) < 850
bot_to_target = agent.info.ball.pos - car.pos
local_bot_to_target = dot(bot_to_target, agent.info.my_car.theta)
angle_front_to_target = math.atan2(local_bot_to_target[1],
local_bot_to_target[0])
close_to_ball = norm(vec2(bot_to_target)) < 850
good_angle = math.radians(-10) < angle_front_to_target < math.radians(10)
return close_to_ball and close_to_goal and aiming_for_goal and good_angle
def shooting_target(agent):
ball = agent.info.ball
car = agent.info.my_car
car_to_ball = ball.pos - car.pos
backline_intersect = line_backline_intersect(
agent.info.their_goal.center[1], vec2(car.pos), vec2(car_to_ball))
if -500 < backline_intersect < 500:
goal_to_ball = normalize(car.pos - ball.pos)
error = cap(distance_2d(ball.pos, car.pos) / 1000, 0, 1)
else:
# Right of the ball
if -500 > backline_intersect:
target = agent.info.their_goal.corners[3] + vec3(400, 0, 0)
# Left of the ball
elif 500 < backline_intersect:
target = agent.info.their_goal.corners[2] - vec3(400, 0, 0)
goal_to_ball = normalize(ball.pos - target)
goal_to_car = normalize(car.pos - target)
difference = goal_to_ball - goal_to_car
error = cap(abs(difference[0]) + abs(difference[1]), 1, 10)
goal_to_ball_2d = vec2(goal_to_ball[0], goal_to_ball[1])
test_vector_2d = dot(rotation(0.5 * math.pi), goal_to_ball_2d)
test_vector = vec3(test_vector_2d[0], test_vector_2d[1], 0)
distance = cap((40 + distance_2d(ball.pos, car.pos) * (error**2)) / 1.8, 0,
4000)
location = ball.pos + vec3(
(goal_to_ball[0] * distance), goal_to_ball[1] * distance, 0)
# this adjusts the target based on the ball velocity perpendicular to the direction we're trying to hit it
multiplier = cap(distance_2d(car.pos, location) / 1500, 0, 2)
distance_modifier = cap(
dot(test_vector, ball.vel) * multiplier, -1000, 1000)
modified_vector = vec3(test_vector[0] * distance_modifier,
test_vector[1] * distance_modifier, 0)
location += modified_vector
# another target adjustment that applies if the ball is close to the wall
extra = 3850 - abs(location[0])
if extra < 0:
location[0] = cap(location[0], -3850, 3850)
location[1] = location[1] + (-sign(agent.team) * cap(extra, -800, 800))
return location
def can_dodge(agent, target):
bot_to_target = target - agent.info.my_car.pos
local_bot_to_target = dot(bot_to_target, agent.info.my_car.theta)
angle_front_to_target = math.atan2(local_bot_to_target[1], local_bot_to_target[0])
distance_bot_to_target = norm(vec2(bot_to_target))
good_angle = math.radians(-10) < angle_front_to_target < math.radians(10)
on_ground = agent.info.my_car.on_ground and agent.info.my_car.pos[2] < 100
going_fast = velocity_2d(agent.info.my_car.vel) > 1250
target_not_in_goal = not agent.info.my_goal.inside(target)
return good_angle and distance_bot_to_target > 2000 and on_ground and going_fast and target_not_in_goal
def distance_2d(a, b):
return norm(vec2(a - b))
def velocity_2d(vel):
return norm(vec2(vel))
def step(self, dt):
# direction of ball relative to center of car (where should we aim)
# direction of ball relative to yaw of car (where should we aim verse where we are aiming)
local_bot_to_ball = dot(self.ball.pos - self.car.pos, self.car.theta)
angle_front_to_ball = math.atan2(local_bot_to_ball[1], local_bot_to_ball[0])
# distance between bot and ball
distance = distance_2d(self.car.pos, self.ball.pos)
# direction of ball velocity relative to yaw of car (which way the ball is moving verse which way we are moving)
if velocity_2d(self.ball.vel) < 1e-10:
angle_car_forward_to_ball_vel = 0
else:
angle_car_forward_to_ball_vel = angle_between(z0(self.car.forward()), z0(self.ball.vel))
# magnitude of ball_bot_angle (squared)
ball_bot_diff = (self.ball.vel[0] ** 2 + self.ball.vel[1] ** 2) - (self.car.vel[0] ** 2 + self.car.vel[1] ** 2)
# p is the distance between ball and car
# i is the magnitude of the ball's velocity (squared) the i term would normally
# be the integral of p over time, but the ball's velocity is essentially that number
# d is the relative speed between ball and car
# note that bouncing a ball is distinctly different than balancing something that doesnt bounce
# p_s is the x component of the distance to the ball
# d_s is the one frame change of p_s, that's why p_s has to be global
# we modify distance and ball_bot_diff so that only the component along the car's path is counted
# if the ball is too far to the left, we don't want the bot to think it has to drive forward
# to catch it
distance_y = math.fabs(distance * math.cos(angle_front_to_ball))
distance_x = math.fabs(distance * math.sin(angle_front_to_ball))
# ball moving forward WRT car yaw?
forward = False
if math.fabs(angle_car_forward_to_ball_vel) < math.radians(90):
forward = True
# first we give the distance values signs
if forward:
d = ball_bot_diff
i = (self.ball.vel[0] ** 2 + self.ball.vel[1] ** 2)
else:
d = -ball_bot_diff
i = -(self.ball.vel[0] ** 2 + self.ball.vel[1] ** 2)
if math.fabs(math.degrees(angle_front_to_ball)) < 90:
p = distance_y
else:
p = -1 * distance_y
# this is the PID correction. all of the callibration goes on right here
# there is literature about how to set the variables but it doesn't work quite the same
# because the car is only touching the ball (and interacting with the system) on bounces
# we run the PID formula through tanh to give a value between -1 and 1 for steering input
# if the ball is lower we have no velocity bias
bias_v = 600000 # 600000
# just the basic PID if the ball is too low
if self.ball.pos[2] < 120:
correction = np.tanh((20 * p + .0015 * i + .006 * d) / 500)
# if the ball is on top of the car we use our bias (the bias is in velocity units squared)
else:
correction = np.tanh((20 * p + .0015 * (i - bias_v) + .006 * d) / 500)
# makes sure we don't get value over .99 so we dont exceed maximum thrust
self.controls.throttle = correction * .99
# anything over .9 is boost
if correction > .99:
self.controls.boost = True
else:
self.controls.boost = False
# this is the PID steering section
# p_s is the x component of the distance to the ball (relative to the cars direction)
# d_s is the on frame change in p_s
# we use absolute value and then set the sign later
d_s = math.fabs(self.p_s) - math.fabs(distance_x)
self.p_s = math.fabs(distance_x)
# give the values the correct sign
if angle_front_to_ball < 0:
self.p_s = -self.p_s
d_s = -d_s
# d_s is actually -d_s ...whoops
d_s = -d_s
max_bias = 35
backline_intersect = line_backline_intersect(self.goal.center[1], vec2(self.car.pos),
vec2(self.car.forward()))
if abs(backline_intersect) < 1000 or self.ball.pos[2] > 200:
bias = 0
# Right of the ball
elif -850 > backline_intersect:
bias = max_bias
# Left of the ball
elif 850 < backline_intersect:
bias = -max_bias
# the correction settings can be altered to change performance
correction = np.tanh((100 * (self.p_s + bias) + 1500 * d_s) / 8000)
# apply the correction
self.controls.steer = correction
def get_controls(self):
if self.step == "Steer" or self.step == "Dodge2":
self.step = "Catching"
if self.step == "Catching":
target = get_bounce(self)
if target is None:
self.step = "Defending"
else:
self.catching.target_pos = target[0]
self.catching.target_speed = (distance_2d(
self.info.my_car.pos, target[0]) + 50) / target[1]
self.catching.step(self.FPS)
self.controls = self.catching.controls
ball = self.info.ball
car = self.info.my_car
if distance_2d(ball.pos,
car.pos) < 150 and 65 < abs(ball.pos[2] -
car.pos[2]) < 127:
self.step = "Dribbling"
self.dribble = Dribbling(self.info.my_car, self.info.ball,
self.info.their_goal)
if self.defending:
self.step = "Defending"
if not self.info.my_car.on_ground:
self.step = "Recovery"
ball = self.info.ball
if abs(ball.vel[2]) < 100 and sign(
self.team) * ball.vel[1] < 0 and sign(
self.team) * ball.pos[1] < 0:
self.step = "Shooting"
elif self.step == "Dribbling":
self.dribble.step(self.FPS)
self.controls = self.dribble.controls
ball = self.info.ball
car = self.info.my_car
bot_to_opponent = self.info.opponents[0].pos - self.info.my_car.pos
local_bot_to_target = dot(bot_to_opponent, self.info.my_car.theta)
angle_front_to_target = math.atan2(local_bot_to_target[1],
local_bot_to_target[0])
opponent_is_near = norm(vec2(bot_to_opponent)) < 2000
opponent_is_in_the_way = math.radians(
-10) < angle_front_to_target < math.radians(10)
if not (distance_2d(ball.pos, car.pos) < 150
and 65 < abs(ball.pos[2] - car.pos[2]) < 127):
self.step = "Catching"
if self.defending:
self.step = "Defending"
if opponent_is_near and opponent_is_in_the_way:
self.step = "Dodge"
self.dodge = AirDodge(self.info.my_car, 0.25,
self.info.their_goal.center)
if not self.info.my_car.on_ground:
self.step = "Recovery"
elif self.step == "Defending":
defending(self)
elif self.step == "Dodge":
self.dodge.step(self.FPS)
self.controls = self.dodge.controls
self.controls.boost = 0
if self.dodge.finished and self.info.my_car.on_ground:
self.step = "Catching"
elif self.step == "Recovery":
self.recovery.step(self.FPS)
self.controls = self.recovery.controls
if self.info.my_car.on_ground:
self.step = "Catching"
elif self.step == "Shooting":
shooting(self)