fix(physics): make upright a real state, and actually start ships on the floor

Six rounds of reward shaping (~700M steps) failed to produce upright ground driving. A critical review of the simulation rather than the reward found why: 1. The hull was a 1x1x4 box with inertia (1,1,1) and no restoring torque anywhere, so belly-down and rolled-90 were geometrically identical resting states. "Upright" was not a physically distinguished state at all - the reward was paying for a property the simulation did not have. 2. ~65% of episodes spawned ships via _random_position, which samples Y uniformly over the full 18m volume (mean ~8.7m). The measured airborne_fraction ~0.44 was largely that spawn distribution, and every ground-handling term fades out above 3m, so the shaping being tuned barely ever applied. 3. air_drill_chance 0.20 spawned deliberately unreachable-without-climbing states in the stage meant to teach ground driving, and its own air_touch_fraction (0.0002) shows the drills were never solved. Fixes land in the physics and the task distribution, not the reward: - ship.tscn: hull 1x1x4 -> 1.6x0.6x4 so it has one stable resting face; inertia (1,1,1) -> (7,1,7), physically correct for the hull, making tumbling reluctant while keeping yaw snappy. - ship.gd: new altitude-faded righting torque (spring-damper toward belly-down, faded out by 3m so aerials keep full attitude freedom). This is the grav-plating analogue of Rocket League's auto-righting and helps human pilots land cleanly too. - training_mode.gd: new ground_start_chance branch spawning ships level and resting on the floor with a floor-level ball - the state the handling stage's rewards are actually written for. - generation5.py: ground-start-chance 0.50, air-drill-chance 0.20 -> 0.0. Reward terms are left exactly as they were; they should finally pull in a direction the ship can go.
2026-09-10 16:04:04 +00:00 · 2026-08-16 08:17:16 +01:00
parent 033a774c92
commit ea756bd5ba
15 changed files with 146 additions and 270 deletions
@@ -9,14 +9,14 @@ friction = 0.1
 bounce = 0.15

 [sub_resource type="BoxShape3D" id="BoxShape3D_dsjou"]
-size = Vector3(1, 1, 4)
+size = Vector3(1.6, 0.6, 4)

 [node name="Ship" type="RigidBody3D"]
 collision_layer = 1
 collision_mask = 7
 mass = 5.0
 physics_material_override = SubResource("PhysicsMaterial_ship")
-inertia = Vector3(1, 1, 1)
+inertia = Vector3(7, 1, 7)
 script = ExtResource("1_efag7")

 [node name="Nose" type="MeshInstance3D" parent="."]
@@ -26,6 +26,21 @@ extends RigidBody3D
@export var ceiling_pull_strength = 11.5 # Ceiling grav-plating strength; nets above gravity so a ship can hold a ceiling
@export var ceiling_pull_range = 3.0     # Metres from the ceiling where pull begins

+# Grav-plating righting torque: a spring-damper that rolls/pitches the hull
+# back toward belly-down, strongest at floor level and faded to nothing by
+# righting_range so genuine aerials keep full attitude freedom. Without it
+# "upright" is not a physically distinguished state at all — the hull is a
+# box with no restoring torque, so belly-down and rolled-90 are equally
+# stable and a policy has no dynamics-level reason to prefer either. Six
+# rounds of RL reward shaping (see TRAINING.md) failed to buy upright
+# ground handling for exactly this reason; the fix belongs in the physics,
+# not the reward. Same idea as the wall/ceiling pull above — the plating
+# orients you, not just attracts you — and it helps human pilots land
+# cleanly too.
+@export var righting_strength: float = 20.0  # Righting spring gain (0 disables)
+@export var righting_damping: float = 6.0    # Opposes tumble while righting
+@export var righting_range: float = 3.0      # Metres above the floor where righting fades out
+
 # Non-tinted hull meshes, runtime-merged into one ArrayMesh by
 # _build_merged_hull() (Nose/TailFin stay separate MeshInstance3Ds since
 # _apply_team_color() retints them per-team and must keep addressing them by
@@ -337,6 +352,7 @@ func _integrate_forces(state):

 	# === ROTATION (Turning) ===
 	apply_rotation_forces(state, _current_action.rotation)
+	apply_righting_torque(state)

 	# === DRAG AND LIMITS ===
 	apply_drag_and_limits(state, _current_action.rotation)
@@ -385,6 +401,31 @@ func apply_surface_pull(state: PhysicsDirectBodyState3D) -> void:
 	state.apply_central_force(pull * mass)


+# Spring-damper torque toward belly-down (see righting_strength). The spring
+# term basis.y x UP is a world-space axis whose magnitude is sin(tilt) and
+# whose direction is the shortest rotation back to upright, so it is zero
+# when already level, peaks on its side, and — being a cross product —
+# vanishes again when perfectly inverted. The damping term is applied only
+# about that same righting axis, so it bleeds off tumble without taxing
+# deliberate yaw. Fades linearly to nothing by righting_range metres up,
+# matching every other ground-handling term's altitude ramp (see
+# ShipAIController.GROUND_HANDLING_HEIGHT).
+func apply_righting_torque(state: PhysicsDirectBodyState3D) -> void:
+	if righting_strength <= 0.0:
+		return
+	var height_factor := 1.0 - clampf(global_position.y / righting_range, 0.0, 1.0)
+	if height_factor <= 0.0:
+		return
+
+	var righting_axis := global_transform.basis.y.cross(Vector3.UP)
+	var torque := righting_axis * righting_strength
+	# Damp only the component of spin around the righting axis.
+	if righting_axis.length_squared() > 0.0001:
+		var axis := righting_axis.normalized()
+		torque -= axis * state.angular_velocity.dot(axis) * righting_damping
+	state.apply_torque(torque * height_factor)
+
+
 func apply_rotation_forces(state: PhysicsDirectBodyState3D, rotation_input: Vector3):
 	if rotation_input.length() < 0.01:
 		return
@@ -69,6 +69,15 @@ extends GameMode
 # a real goal and ships start low behind/lateral to it, so a useful touch is
 # naturally reinforced by the existing goal-directed ball rewards.
@export_range(0.0, 1.0) var air_intercept_chance := 0.0
+# Ground-start branch for the generation-5 handling stage: ships spawn level
+# and resting on the floor with a low, floor-level ball. Every other branch
+# samples ship Y uniformly across the full 18m volume (see _random_position),
+# so ~65% of episodes previously began at a mean altitude near 8.7m — the
+# measured airborne_fraction ~0.44 was largely that spawn distribution rather
+# than a policy preference, and the ground-handling reward terms (which all
+# fade out above 3m) barely ever applied. A stage that means to teach driving
+# has to actually start the ship on the ground.
+@export_range(0.0, 1.0) var ground_start_chance := 0.0

 # Ships per team. Default 1 preserves every existing curriculum script's 1v1
 # behaviour unchanged; up to 5 matches ShipObservations.MAX_TEAMMATES/
@@ -77,13 +86,19 @@ extends GameMode
@export_range(1, 5) var team_size: int = 1

 # Placement bounds for randomized episode starts, derived from the standard
-# enclosure (ArenaBoundary). The inset keeps a randomly oriented ship (1x1x4
-# box, worst-case half-extent ~2.05) from spawning intersecting the walls,
-# ceiling, or goal sensors.
+# enclosure (ArenaBoundary). The inset keeps a randomly oriented ship
+# (1.6x0.6x4 box, worst-case half-extent ~2.18) from spawning intersecting
+# the walls, ceiling, or goal sensors.
 const SPAWN_INSET := 2.5
 const FIELD_HALF_X := ArenaBoundary.INNER_HALF_X - SPAWN_INSET
 const FIELD_HALF_Z := ArenaBoundary.GOAL_LINE_Z - SPAWN_INSET
 const FIELD_MIN_Y := 1.5
+# Resting heights for the ground-start branch: half the ship hull's 0.6 height
+# and the ball's 0.5 radius (Godot's SphereShape3D default, see ball.tscn),
+# each plus a little clearance so bodies settle onto the floor instead of
+# spawning interpenetrated with it.
+const GROUND_START_Y := 0.35
+const GROUND_START_BALL_Y := 0.55
 const FIELD_MAX_Y := ArenaBoundary.INNER_HEIGHT - SPAWN_INSET
 # The corner curves reach at most their chord plane |x| + |z| = INNER_HALF_X
 # + INNER_HALF_Z - CORNER_RADIUS; spawns keep the same SPAWN_INSET clearance
@@ -243,7 +258,7 @@ func _parse_eval_args() -> void:
 const TRAINING_MODE_OVERRIDES := [
 	"goal_reward", "draw_penalty", "kickoff_state_chance",
 	"ball_near_goal_chance", "attack_goal_bias", "air_drill_chance",
-	"air_intercept_chance", "team_size",
+	"air_intercept_chance", "ground_start_chance", "team_size",
 ]
 # ShipAIController @export names a curriculum run may override, read as
 # --ai_<name>=<value> to avoid colliding with the names above.
@@ -273,6 +288,7 @@ func _parse_curriculum_args() -> void:
 			set(name, _typed_like(args[name], get(name)))
 	var start_probability := kickoff_state_chance + ball_near_goal_chance \
 		+ air_drill_chance + air_intercept_chance
+	start_probability += ground_start_chance
 	if start_probability > 1.0:
 		push_error("TrainingMode: episode-start probabilities sum to %.3f (> 1.0)" % start_probability)

@@ -428,6 +444,9 @@ func _reset_episode() -> void:
 		_place_air_drill()
 	elif roll < kickoff_state_chance + ball_near_goal_chance + air_drill_chance + air_intercept_chance:
 		_place_air_intercept()
+	elif roll < kickoff_state_chance + ball_near_goal_chance + air_drill_chance \
+			+ air_intercept_chance + ground_start_chance:
+		_place_ground_start()
 	else:
 		_place_ships_random()
 		_place_ball_random()
@@ -497,6 +516,46 @@ func _place_air_drill() -> void:
 		_place_body(ship, Transform3D(orientation, ship_position), Vector3.ZERO, Vector3.ZERO)


+# Ground start (see ground_start_chance): ships resting level on the floor,
+# yaw-only so they begin belly-down rather than needing to recover attitude
+# first, and a floor-level ball rolling slowly. This is the state the
+# handling stage's rewards are actually written for — every ground term
+# (ground_tilt_penalty, non_forward_penalty, the nose-led approach bonus)
+# fades out by GROUND_HANDLING_HEIGHT, so they only bite in states like this
+# one. The ball gets a modest planar-only velocity so it stays reachable
+# without a climb.
+func _place_ground_start() -> void:
+	var ball_velocity := _random_direction()
+	ball_velocity.y = 0.0
+	ball_velocity = ball_velocity.normalized() * randf_range(0.0, MAX_RANDOM_BALL_SPEED * 0.5)
+	var ball_position := Vector3(
+		randf_range(-FIELD_HALF_X, FIELD_HALF_X),
+		GROUND_START_BALL_Y,
+		randf_range(-FIELD_HALF_Z, FIELD_HALF_Z)
+	)
+	_place_body(ball, Transform3D(Basis.IDENTITY, ball_position), ball_velocity, Vector3.ZERO)
+
+	var placed: Array[Vector3] = []
+	for ship in ships:
+		if ship in _inert_ships:
+			continue
+		var ship_position := Vector3.ZERO
+		for _attempt in 20:
+			ship_position = Vector3(
+				randf_range(-FIELD_HALF_X, FIELD_HALF_X),
+				GROUND_START_Y,
+				randf_range(-FIELD_HALF_Z, FIELD_HALF_Z)
+			)
+			if _spawn_position_clear(ship_position) and _far_enough_from(ship_position, placed):
+				break
+		placed.append(ship_position)
+		var yaw := randf_range(-PI, PI)
+		_place_body(
+			ship, Transform3D(Basis.from_euler(Vector3(0.0, yaw, 0.0)), ship_position),
+			Vector3.ZERO, Vector3.ZERO
+		)
+
+
 # Goal-relevant aerial intercept: a high ball is already travelling toward a
 # randomly selected goal, while ships begin low and behind/lateral to its
 # path. The generous wall clearance prevents rebound farming and an upright
@@ -122,6 +122,35 @@ STANDING_ARGS = ["--ent-coef", "0.01", "--entropy-floor"]
 # so it likely cannot measure the behaviour the 0.45 floor was meant to
 # capture. Re-baseline that floor from what the new signal reports rather
 # than from another round of reshaping.
+#
+# Round 6 (2026-08-16): round 5 read grounded_upright_fraction 0.050 /
+# 0.069 / 0.052 — when the ship touches the floor it is upright about 1
+# time in 17 — and the user's own observation was "it spends the vast
+# majority of the time on its side, driving upwards towards the ball". A
+# critical review of the *simulation* rather than the reward found why six
+# rounds of shaping could never work:
+#
+#   1. The hull was a 1x1x4 box with inertia (1,1,1) and no restoring
+#      torque anywhere, so belly-down and rolled-90 were geometrically
+#      identical resting states. "Upright" was not a physically
+#      distinguished state at all — the reward was paying for a property
+#      the simulation did not have.
+#   2. ~65% of episodes spawned ships from _random_position, which samples
+#      Y uniformly over the full 18m volume (mean ~8.7m). The measured
+#      airborne_fraction ~0.44 was largely that spawn distribution, and
+#      every ground-handling term fades out above 3m, so the shaping
+#      being tuned barely ever applied.
+#   3. air_drill_chance 0.20 spawned deliberately unreachable-without-
+#      climbing states in the stage meant to teach ground driving, and its
+#      own air_touch_fraction (0.0002) shows the drills were never solved.
+#
+# Fixes land in the physics and the task distribution instead of the
+# reward: an altitude-faded righting torque plus a flat-bottomed hull and
+# realistic inertia (ship.gd / ship.tscn) make belly-down a genuine
+# attractor, ground_start_chance 0.50 actually starts the ship on the
+# floor, and air-drill-chance goes to 0. The reward terms already built
+# are left exactly as they were — they should finally pull in a direction
+# the ship can go.
 HANDLING_REWARD_FLAGS = [
    "--velocity-to-ball-weight", "0.04",
    "--forward-velocity-to-ball-weight", "0.15",
@@ -145,8 +174,9 @@ STAGES = [
            "--opponent-mode", "self_play",
            "--kickoff-chance", "0.15",
            "--near-goal-chance", "0.25",
-            "--air-drill-chance", "0.20",
+            "--air-drill-chance", "0.0",
            "--air-intercept-chance", "0.0",
+            "--ground-start-chance", "0.50",
            *HANDLING_REWARD_FLAGS,
        ],
        # Conservative catastrophe floors, not claims of mastery. Tail values
@@ -1,263 +1,6 @@
 {
  "stage_index": 0,
-  "attempt": 2,
-  "status": "blocked",
-  "log": [
-    {
-      "stage_index": 0,
-      "stage_number": 4,
-      "stage_name": "handling",
-      "experiment": "20260814-1939-gen5-s4-handling",
-      "attempt": 0,
-      "telemetry_tail": {
-        "rollout/air_touch_fraction": 0.0004599999897181988,
-        "rollout/airborne_fraction": 0.43958361899852755,
-        "rollout/ep_len_mean": 137.3482799835205,
-        "rollout/ep_rew_mean": -9.079601858139037,
-        "rollout/forward_motion_fraction": 0.2240593806952238,
-        "rollout/goal_rate": 0.5860000020265579,
-        "rollout/grounded_upright_fraction": 0.049944999784231184,
-        "rollout/mean_altitude": 4.377092701435089,
-        "rollout/productive_air_touch_fraction": 3.999999910593033e-05,
-        "rollout/upright_fraction": 0.2692298571616411,
-        "rollout/vertical_thrust_mean": 0.11654999937745743
-      },
-      "telemetry_failures": [
-        "rollout/goal_rate=0.5860 < 0.8000",
-        "rollout/upright_fraction=0.2692 < 0.4500",
-        "rollout/forward_motion_fraction=0.2241 < 0.2500"
-      ],
-      "evaluation_goal_failures": [
-        "easy.json: goal_rate=0.780 < 0.800"
-      ],
-      "side_balance_failures": [],
-      "eval": {
-        "timestamp": "2026-08-15T00:56:25+00:00",
-        "model_a": "/home/jcreek/ai-training/CosmicClash/Game/bots/20260814-1939-gen5-s4-handling.json",
-        "model_b": "/home/jcreek/ai-training/CosmicClash/Game/bots/promoted/easy.json",
-        "seed": 1,
-        "episodes": 100,
-        "wins_a": 47,
-        "wins_b": 31,
-        "draws": 22,
-        "side_results": {
-          "a_team_0": {
-            "wins_a": 26,
-            "wins_b": 16,
-            "draws": 8
-          },
-          "a_team_1": {
-            "wins_a": 21,
-            "wins_b": 15,
-            "draws": 14
-          }
-        },
-        "physical_team_wins": {
-          "team_0": 41,
-          "team_1": 37
-        },
-        "win_rate_a": 0.47
-      },
-      "evals": [
-        {
-          "timestamp": "2026-08-15T00:56:25+00:00",
-          "model_a": "/home/jcreek/ai-training/CosmicClash/Game/bots/20260814-1939-gen5-s4-handling.json",
-          "model_b": "/home/jcreek/ai-training/CosmicClash/Game/bots/promoted/easy.json",
-          "seed": 1,
-          "episodes": 100,
-          "wins_a": 47,
-          "wins_b": 31,
-          "draws": 22,
-          "side_results": {
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-              "wins_b": 16,
-              "draws": 8
-            },
-            "a_team_1": {
-              "wins_a": 21,
-              "wins_b": 15,
-              "draws": 14
-            }
-          },
-          "physical_team_wins": {
-            "team_0": 41,
-            "team_1": 37
-          },
-          "win_rate_a": 0.47
-        }
-      ],
-      "decision": "fail"
-    },
-    {
-      "stage_index": 0,
-      "stage_number": 4,
-      "stage_name": "handling",
-      "experiment": "20260815-0156-gen5-s4-handling-retry1",
-      "attempt": 1,
-      "telemetry_tail": {
-        "rollout/air_touch_fraction": 0.0001599999964237213,
-        "rollout/airborne_fraction": 0.4403798085451126,
-        "rollout/ep_len_mean": 142.34064038085938,
-        "rollout/ep_rew_mean": -5.766011684894562,
-        "rollout/forward_motion_fraction": 0.22267090499401093,
-        "rollout/goal_rate": 0.5380800016522408,
-        "rollout/grounded_upright_fraction": 0.06886999988555909,
-        "rollout/mean_altitude": 4.340883392333985,
-        "rollout/productive_air_touch_fraction": 3.999999910593033e-05,
-        "rollout/upright_fraction": 0.300410619109869,
-        "rollout/vertical_thrust_mean": 0.060687998470733875
-      },
-      "telemetry_failures": [
-        "rollout/goal_rate=0.5381 < 0.8000",
-        "rollout/upright_fraction=0.3004 < 0.4500",
-        "rollout/forward_motion_fraction=0.2227 < 0.2500"
-      ],
-      "evaluation_goal_failures": [],
-      "side_balance_failures": [],
-      "eval": {
-        "timestamp": "2026-08-15T07:12:56+00:00",
-        "model_a": "/home/jcreek/ai-training/CosmicClash/Game/bots/20260815-0156-gen5-s4-handling-retry1.json",
-        "model_b": "/home/jcreek/ai-training/CosmicClash/Game/bots/promoted/easy.json",
-        "seed": 1,
-        "episodes": 100,
-        "wins_a": 48,
-        "wins_b": 32,
-        "draws": 20,
-        "side_results": {
-          "a_team_0": {
-            "wins_a": 22,
-            "wins_b": 17,
-            "draws": 11
-          },
-          "a_team_1": {
-            "wins_a": 26,
-            "wins_b": 15,
-            "draws": 9
-          }
-        },
-        "physical_team_wins": {
-          "team_0": 37,
-          "team_1": 43
-        },
-        "win_rate_a": 0.48
-      },
-      "evals": [
-        {
-          "timestamp": "2026-08-15T07:12:56+00:00",
-          "model_a": "/home/jcreek/ai-training/CosmicClash/Game/bots/20260815-0156-gen5-s4-handling-retry1.json",
-          "model_b": "/home/jcreek/ai-training/CosmicClash/Game/bots/promoted/easy.json",
-          "seed": 1,
-          "episodes": 100,
-          "wins_a": 48,
-          "wins_b": 32,
-          "draws": 20,
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-              "wins_b": 15,
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-            }
-          },
-          "physical_team_wins": {
-            "team_0": 37,
-            "team_1": 43
-          },
-          "win_rate_a": 0.48
-        }
-      ],
-      "decision": "fail"
-    },
-    {
-      "stage_index": 0,
-      "stage_number": 4,
-      "stage_name": "handling",
-      "experiment": "20260815-0812-gen5-s4-handling-retry2",
-      "attempt": 2,
-      "telemetry_tail": {
-        "rollout/air_touch_fraction": 0.0002199999950826168,
-        "rollout/airborne_fraction": 0.4502894285917282,
-        "rollout/ep_len_mean": 141.1317198638916,
-        "rollout/ep_rew_mean": -4.833696460247039,
-        "rollout/forward_motion_fraction": 0.2373267139494419,
-        "rollout/goal_rate": 0.5526000013351441,
-        "rollout/grounded_upright_fraction": 0.051729999739676714,
-        "rollout/mean_altitude": 4.42696008014679,
-        "rollout/productive_air_touch_fraction": 7.999999821186065e-05,
-        "rollout/upright_fraction": 0.2735673332810402,
-        "rollout/vertical_thrust_mean": 0.08471799899730831
-      },
-      "telemetry_failures": [
-        "rollout/goal_rate=0.5526 < 0.8000",
-        "rollout/upright_fraction=0.2736 < 0.4500",
-        "rollout/forward_motion_fraction=0.2373 < 0.2500"
-      ],
-      "evaluation_goal_failures": [
-        "easy.json: goal_rate=0.740 < 0.800"
-      ],
-      "side_balance_failures": [],
-      "eval": {
-        "timestamp": "2026-08-15T13:29:47+00:00",
-        "model_a": "/home/jcreek/ai-training/CosmicClash/Game/bots/20260815-0812-gen5-s4-handling-retry2.json",
-        "model_b": "/home/jcreek/ai-training/CosmicClash/Game/bots/promoted/easy.json",
-        "seed": 1,
-        "episodes": 100,
-        "wins_a": 44,
-        "wins_b": 30,
-        "draws": 26,
-        "side_results": {
-          "a_team_0": {
-            "wins_a": 21,
-            "wins_b": 18,
-            "draws": 11
-          },
-          "a_team_1": {
-            "wins_a": 23,
-            "wins_b": 12,
-            "draws": 15
-          }
-        },
-        "physical_team_wins": {
-          "team_0": 33,
-          "team_1": 41
-        },
-        "win_rate_a": 0.44
-      },
-      "evals": [
-        {
-          "timestamp": "2026-08-15T13:29:47+00:00",
-          "model_a": "/home/jcreek/ai-training/CosmicClash/Game/bots/20260815-0812-gen5-s4-handling-retry2.json",
-          "model_b": "/home/jcreek/ai-training/CosmicClash/Game/bots/promoted/easy.json",
-          "seed": 1,
-          "episodes": 100,
-          "wins_a": 44,
-          "wins_b": 30,
-          "draws": 26,
-          "side_results": {
-            "a_team_0": {
-              "wins_a": 21,
-              "wins_b": 18,
-              "draws": 11
-            },
-            "a_team_1": {
-              "wins_a": 23,
-              "wins_b": 12,
-              "draws": 15
-            }
-          },
-          "physical_team_wins": {
-            "team_0": 33,
-            "team_1": 41
-          },
-          "win_rate_a": 0.44
-        }
-      ],
-      "decision": "fail"
-    }
-  ]
+  "attempt": 0,
+  "status": "in_progress",
+  "log": []
 }
@@ -334,6 +334,11 @@ def parse_args():
        "--air-intercept-chance", type=float, default=None,
        help="Moving high-ball interception starts aimed at a real goal (generation-5 aerial stage)",
    )
+    curriculum.add_argument(
+        "--ground-start-chance", type=float, default=None,
+        help="Fraction of resets that spawn ships level and resting on the floor with a floor-level "
+        "ball — the state the handling stage's ground rewards are written for",
+    )
    curriculum.add_argument(
        "--team-size", type=int, choices=range(1, 6), default=None,
        help="Ships per team (1-5); generation-5 automated stages remain 1v1 until 2v2 evaluation exists",
@@ -406,6 +411,7 @@ def _curriculum_kwargs(args) -> dict:
        "ball_near_goal_chance": args.near_goal_chance,
        "air_drill_chance": args.air_drill_chance,
        "air_intercept_chance": args.air_intercept_chance,
+        "ground_start_chance": args.ground_start_chance,
        "team_size": args.team_size,
        "ai_tilt_penalty": args.tilt_penalty,
        "ai_ground_tilt_penalty": args.ground_tilt_penalty,