def estimate_time(car: Car, target, dd=1) -> float:
turning_radius = 1 / Drive.max_turning_curvature(norm(car.velocity) + 500)
turning = angle_between(car.forward() * dd, direction(
car, target)) * turning_radius / 1800
if turning < 0.5: turning = 0
dist = ground_distance(car, target) - 200
if dist < 0: return turning
speed = dot(car.velocity, car.forward())
time = 0
result = None
if car.boost > 0 and dd > 0:
boost_time = car.boost / 33.33
result = BOOST.simulate_until_limit(speed,
distance_limit=dist,
time_limit=boost_time)
dist -= result.distance_traveled
time += result.time_passed
speed = result.speed_reached
if dist > 0 and speed < 1410:
result = THROTTLE.simulate_until_limit(speed, distance_limit=dist)
dist -= result.distance_traveled
time += result.time_passed
speed = result.speed_reached
if result is None or not result.distance_limit_reached:
time += dist / speed
return time * 1.05 + turning
def estimate_time(car: Car, target, speed, dd=1) -> float:
dist = distance(car, target)
if dist < 100:
return 0
travel = dist / speed
turning = angle_between(car.forward() * dd, direction(car, target)) / math.pi * 2
if turning < 1:
turning **= 2
acceleration = (speed * dd - dot(car.velocity, car.forward())) / 2100 * 0.2 * dd / max(car.boost / 20, 1)
return travel + acceleration + turning * 0.7
def toPoint(car: Car, target: vec3):
direction = normalize(target - car.position)
turnAngleAmount = math.acos(
max(-1, min(1, dot(car.forward(), direction))))
rotateToZeroAngle = -atan2(direction)
towardsZeroVector = rotate2(car.forward(), rotateToZeroAngle)
turnDirection = math.copysign(1, -towardsZeroVector[1])
return PID.fromAngle(car, turnAngleAmount * turnDirection)
def toPointReverse(car: Car, target: vec3):
direction = normalize(target - car.position)
turnAngleAmount = math.acos(
max(-1, min(1, -dot(car.forward(), direction))))
rotateToZeroAngle = -atan2(direction)
towardsZeroVector = rotate2(car.forward(), rotateToZeroAngle + math.pi)
turnDirection = math.copysign(1, towardsZeroVector[1])
ANGLETERM = 3.5
ANGULARTERM = -0.3
angleP = turnDirection * min(2, ANGLETERM * turnAngleAmount)
angleD = ANGULARTERM * car.angular_velocity[2]
return min(1, max(-1, angleP + angleD))
def align(car: Car, target: vec3, direction: vec3):
turnAngleAmount = math.acos(dot(car.forward(), direction))
rotateToZeroAngle = -atan2(direction)
posOffset = rotate2(target - car.position, rotateToZeroAngle)
towardsZeroVector = rotate2(car.forward(), rotateToZeroAngle)
turnDirection = math.copysign(1, -towardsZeroVector[1])
turnRadius = 1 / RLUDrive.max_turning_curvature(norm(car.velocity))
ANGLETERM = 10
ANGULARTERM = -0.3
CORRECTIONTERM = 1 / 40
angleP = turnDirection * min(2, ANGLETERM * turnAngleAmount)
angleD = ANGULARTERM * car.angular_velocity[2]
finalOffset = posOffset[1] + turnDirection * turnRadius / .85 * (
1 - math.cos(turnAngleAmount))
offsetCorrection = CORRECTIONTERM * finalOffset
return min(1, max(-1, angleP + angleD + offsetCorrection))
def __init__(self, car: Car, use_boost=False):
self.car = car
self.use_boost = use_boost
self.controls = Input()
self.dodge = Dodge(car)
self.dodge.duration = 0.12
self.dodge.direction = vec2(car.forward() * (-1))
self.s = 0.95 * sgn(
dot(self.car.angular_velocity, self.car.up()) + 0.01)
self.timer = 0.0
self.finished = False
def get_controls(self, car_state: CarState, car: Car):
controls = SimpleControllerState()
target_Vec3 = Vec3(self.location[0], self.location[1],
self.location[2])
if angle_between(self.location - to_vec3(car_state.physics.location),
car.forward()) > pi / 2:
controls.boost = False
controls.handbrake = True
elif angle_between(self.location - to_vec3(car_state.physics.location),
car.forward()) > pi / 4:
controls.boost = False
controls.handbrake = False
else:
controls.boost = self.boost
controls.handbrake = False
# Be smart about not using boost at max speed
# if Vec3(car.physics.velocity).length() > self.boost_analysis.frames[-1].speed - 10:
# controls.boost = False
controls.steer = steer_toward_target(car_state, target_Vec3)
controls.throttle = 1
return controls
def __init__(self, car: Car, target: vec3 = vec3(0, 0, 0), waste_boost=False):
super().__init__(car)
self.target = Arena.clamp(ground(target), 100)
self.waste_boost = waste_boost
self.finish_distance = 500
self._time_on_ground = 0
self.driving = True
# decide whether to start driving backwards and halfflip later
forward_estimate = estimate_time(car, self.target)
backwards_estimate = estimate_time(car, self.target, -1) + 0.5
backwards = (
dot(car.velocity, car.forward()) < 500
and backwards_estimate < forward_estimate
and (distance(car, self.target) > 3000 or distance(car, self.target) < 300)
and car.position[2] < 200
)
self.drive = Drive(car, self.target, 2300, backwards)
self.action = self.drive
def calculate(car: Car, ball: Ball, target: vec3, ball_predictions=None):
# Init vars
b = Ball(ball)
dt = 1.0 / 60.0
# Generate predictions of ball path
if ball_predictions is None:
ball_predictions = []
for i in range(60 * 5):
b.step(dt)
ball_predictions.append(vec3(b.location))
# Gradually converge on ball location by aiming at a location, checking time to that location,
# and then aiming at the ball's NEW position. Guaranteed to converge (typically in <10 iterations)
# unless the ball is moving away from the car faster than the car's max boost speed
intercept = Intercept(b.location)
intercept.purpose = 'ball'
intercept.boost = True
intercept_ball_position = vec3(b.location)
collision_achieved = False
last_horizontal_error = None
last_horizontal_offset = None
i = 0
max_tries = 101
analyzer = BoostAnalysis() if intercept.boost else ThrottleAnalysis()
while i < max_tries:
i += 1
fake_car = Car(car)
direction = normalize(intercept.location - car.location)
fake_car.rotation = look_at(direction, fake_car.up())
for t in range(60 * 5):
# Step car location with throttle/boost analysis data
# Not super efficient but POITROAE
frame = analyzer.travel_time(dt, norm(fake_car.velocity))
# print('in 1 frame I travel', frame.time, frame.distance, frame.speed)
fake_car.location += direction * frame.distance
fake_car.velocity = direction * frame.speed
fake_car.time += dt
ball_location = ball_predictions[t]
# Check for collision
p = closest_point_on_obb(fake_car.hitbox(), ball_location)
if norm(p - ball_location) <= ball.collision_radius:
direction_vector = p - (fake_car.location - normalize(
fake_car.forward()) * 13.88) # octane center of mass
direction_vector[2] = 0
target_direction_vector = target - ball_location
target_direction_vector[2] = 0
intercept_ball_position = ball_location
direction = atan2(direction_vector[1], direction_vector[0])
ideal_direction = atan2(target_direction_vector[1],
target_direction_vector[0])
horizontal_error = direction - ideal_direction
# intercept.location = vec3(ball_location)
# intercept.time = fake_car.time
# return intercept
# Now descend the hit direction gradient
# Kick off the gradient descent with an arbitrary seed value
if last_horizontal_error is None:
last_horizontal_error = horizontal_error
last_horizontal_offset = 0
if horizontal_error > 0:
horizontal_offset = 25
else:
horizontal_offset = 25
intercept.location = ball_location - normalize(
fake_car.left()) * horizontal_offset
break
# Recursive case of gradient descent
if horizontal_offset == last_horizontal_offset:
gradient = 0
else:
gradient = (horizontal_error - last_horizontal_error
) / (horizontal_offset -
last_horizontal_offset)
if gradient == 0:
predicted_horizontal_offset = horizontal_offset
else:
predicted_horizontal_offset = horizontal_offset - horizontal_error / gradient
# Base case (convergence)
if abs(gradient) < 0.0005:
print(f'convergence in {i} iterations')
print(f'gradient = {gradient}')
print(
f'last_horizontal_offset = {last_horizontal_offset}'
)
print(f'direction = {degrees(direction)}')
print(f'ideal direction = {degrees(ideal_direction)}')
print(f'target = {target}')
print(f'ball_location = {ball_location}')
return intercept
# Edge case exit: offset maxed out
max_horizontal_offset = car.hitbox(
).half_width[1] + ball.collision_radius
if predicted_horizontal_offset > max_horizontal_offset:
predicted_horizontal_offset = max_horizontal_offset
elif predicted_horizontal_offset < -max_horizontal_offset:
predicted_horizontal_offset = -max_horizontal_offset
last_horizontal_offset = horizontal_offset
last_horizontal_error = horizontal_error
horizontal_offset = predicted_horizontal_offset
# Return the latest intercept location and continue descending the gradient
intercept.location = ball_location - normalize(
fake_car.left()) * predicted_horizontal_offset
print(f'iteration {i}')
print(f'gradient = {gradient}')
print(f'horizontal_offset = {horizontal_offset}')
print(f'horizontal_error = {degrees(horizontal_error)}')
# print(f'ideal direction = {degrees(ideal_direction)}')
break
# Check for arrival
if norm(fake_car.location -
intercept.location) < ball.collision_radius / 2:
intercept.location = ball_location
break
if i >= max_tries:
print(
f'Warning: max tries ({max_tries}) exceeded for calculating intercept'
)
return intercept
def get_car_front_center(car: Car):
return car.location + normalize(car.forward()) * car.hitbox(
).half_width[0] + normalize(car.up()) * car.hitbox().half_width[2]
def angle_to(car: Car, target: vec3, backwards=False) -> float:
return abs(angle_between(xy(car.forward()) * (-1 if backwards else 1), ground_direction(car.position, target)))
def simulate(self, global_target=None):
lol = 0
# Initialize the ball prediction
# Estimate the probable duration of the jump and round it down to the floor decimal
ball_prediction = self.get_ball_prediction_struct()
if self.info.my_car.boost < 6:
duration_estimate = math.floor(
get_time_at_height(self.info.ball.position[2]) * 10) / 10
else:
adjacent = norm(
vec2(self.info.my_car.position - self.info.ball.position))
opposite = (self.info.ball.position[2] -
self.info.my_car.position[2])
theta = math.atan(opposite / adjacent)
t = get_time_at_height_boost(self.info.ball.position[2], theta,
self.info.my_car.boost)
duration_estimate = (math.ceil(t * 10) / 10)
# Loop for 6 frames meaning adding 0.1 to the estimated duration. Keeps the time constraint under 0.3s
for i in range(6):
# Copy the car object and reset the values for the hitbox
car = Car(self.info.my_car)
# Create a dodge object on the copied car object
# Direction is from the ball to the enemy goal
# Duration is estimated duration plus the time added by the for loop
# preorientation is the rotation matrix from the ball to the goal
# TODO make it work on both sides
# Test with preorientation. Currently it still picks a low duration at a later time meaning it
# wont do any of the preorientation.
dodge = Dodge(car)
prediction_slice = ball_prediction.slices[round(
60 * (duration_estimate + i / 60))]
physics = prediction_slice.physics
ball_location = vec3(physics.location.x, physics.location.y,
physics.location.z)
# ball_location = vec3(0, ball_y, ball_z)
dodge.duration = duration_estimate + i / 60
if dodge.duration > 1.4:
break
if global_target is not None:
dodge.direction = vec2(global_target - ball_location)
target = vec3(vec2(global_target)) + vec3(
0, 0, jeroens_magic_number * ball_location[2])
dodge.preorientation = look_at(target - ball_location,
vec3(0, 0, 1))
else:
dodge.target = ball_location
dodge.direction = vec2(ball_location) + vec2(ball_location -
car.position)
dodge.preorientation = look_at(ball_location, vec3(0, 0, 1))
# Loop from now till the end of the duration
fps = 30
for j in range(round(fps * dodge.duration)):
lol = lol + 1
# Get the ball prediction slice at this time and convert the location to RLU vec3
prediction_slice = ball_prediction.slices[round(60 * j / fps)]
physics = prediction_slice.physics
ball_location = vec3(physics.location.x, physics.location.y,
physics.location.z)
dodge.step(1 / fps)
T = dodge.duration - dodge.timer
if T > 0:
if dodge.timer < 0.2:
dodge.controls.boost = 1
dodge.controls.pitch = 1
else:
xf = car.position + 0.5 * T * T * vec3(
0, 0, -650) + T * car.velocity
delta_x = ball_location - xf
if angle_between(vec2(car.forward()),
dodge.direction) < 0.3:
if norm(delta_x) > 50:
dodge.controls.boost = 1
dodge.controls.throttle = 0.0
else:
dodge.controls.boost = 0
dodge.controls.throttle = clip(
0.5 * (200 / 3) * T * T, 0.0, 1.0)
else:
dodge.controls.boost = 0
dodge.controls.throttle = 0.0
else:
dodge.controls.boost = 0
car.step(dodge.controls, 1 / fps)
succesfull = self.dodge_succesfull(car, ball_location, dodge)
if succesfull is not None:
if succesfull:
return True, j / fps, ball_location
else:
break
return False, None, None
