Rename multi-segment functions to two-concept names; polish docstrings

Naming pass: rename functions whose third+ segment is redundant or
implementation-detail, sticking to the codebase's preferred
``noun_verb`` / ``verb_noun`` two-concept idiom. Renames are atomic
across definitions, callers, and tests.

  is_penned_position        →  is_penned
  modulate_speed_near_sheep →  modulate_speed
  mecanum_kinematics_step   →  mecanum_step
  policy_forward_mean       →  forward_mean

Two-concept patterns like ``velocity_to_wheels`` / ``detections_from_scan``
/ ``make_strombom_predictor`` are left alone — they're idiomatic
converters / factories that read as a single concept, and the longer
form aids grep-ability.

Docstring polish:
* ``herding/config.py`` header drops the "previously lived as a
  module-level literal" historical framing — we ship as a single
  thing, so the refactor anecdote no longer earns its keep. The
  usage examples now mention both ``HERDING_WEBOTS`` and
  ``HERDING_MEC_WEBOTS`` presets.

126 pytest cases still pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

training/herding_env.py

@@ -28,7 +28,7 @@ from gymnasium import spaces
 
 from herding.world.diffdrive import (
     heading_speed_to_wheels, kinematics_step,
-    mecanum_kinematics_step, velocity_to_mecanum_wheels, velocity_to_wheels,
+    mecanum_step, velocity_to_mecanum_wheels, velocity_to_wheels,
 )
 from herding.world.flocking_sim import (
     FLEE_SPEED, MAX_SPEED, WANDER_SPEED, compute_heading_speed,
@@ -40,7 +40,7 @@ from herding.world.geometry import (
     GATE_X, GATE_Y, MAX_SHEEP,
     PEN_ENTRY, PEN_X, PEN_Y,
     SHEEP_MAX_WHEEL_OMEGA, SHEEP_WHEEL_BASE, SHEEP_WHEEL_RADIUS,
-    WEBOTS_DT, clip_to_field, is_penned_position,
+    WEBOTS_DT, clip_to_field, is_penned,
 )
 from herding.perception.lidar_perception import detections_from_scan
 from herding.perception.lidar_sim import simulate_scan
@@ -302,7 +302,7 @@ class HerdingEnv(gym.Env):
                                  if robot_cfg is not None else 1.0)
             strafe_bleed = (robot_cfg.strafe_to_forward_bleed
                             if robot_cfg is not None else 0.0)
-            self.dog_x, self.dog_y, self.dog_heading = mecanum_kinematics_step(
+            self.dog_x, self.dog_y, self.dog_heading = mecanum_step(
                 self.dog_x, self.dog_y, self.dog_heading,
                 w_fl, w_fr, w_rl, w_rr,
                 DOG_WHEEL_RADIUS,
@@ -337,7 +337,7 @@ class HerdingEnv(gym.Env):
             self._step_one_sheep(i)
         for i in range(self.n_sheep):
             if (not self.sheep_penned[i]
-                    and is_penned_position(self.sheep_x[i], self.sheep_y[i])):
+                    and is_penned(self.sheep_x[i], self.sheep_y[i])):
                 self.sheep_penned[i] = True
 
         # LiDAR perception runs after sheep move; feeds the obs and the