72 lines
2.6 KiB
Python
72 lines
2.6 KiB
Python
"""
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ml/run_eval_training.py - Benchmark reward system across all curriculum phases.
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"""
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import time
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import numpy as np
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from ml.env import JackBotEnv, CurriculumPhase
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import sys
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from pathlib import Path
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sys.path.append(str(Path(__file__).resolve().parent.parent))
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def evaluate_kinematics(episode_length: int = 1000):
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env = JackBotEnv(
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use_gui=True,
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random_command=False,
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max_episode_steps=episode_length,
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robot_mode="kinematics"
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)
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print("\n" + "=" * 70)
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print(" RUNNING MULTI-PHASE REWARD BENCHMARK (KINEMATICS MODE)")
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print("=" * 70 + "\n")
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phase_configs = [
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(CurriculumPhase.FORWARD, "FORWARD GAIT", np.array([1.0, 0.0, 0.0], dtype=np.float32)),
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(CurriculumPhase.TURN_AND_DIRECTION, "FORWARD + YAW TURN", np.array([0.5, 0.0, 0.4], dtype=np.float32)),
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(CurriculumPhase.OMNI_DIRECTION, "STRIDE LATERAL", np.array([0.5, 0.5, 0.0], dtype=np.float32)),
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(CurriculumPhase.FULL_COMMAND, "FULL OMNI COMBINATION",np.array([0.3, 0.2, 0.3], dtype=np.float32)),
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]
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for phase_enum, label, cmd in phase_configs:
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obs, _ = env.reset()
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env.curriculum_phase = phase_enum
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env.command = cmd.copy()
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done = False
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total_reward = 0.0
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step_count = 0
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while not done:
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dummy_action = np.zeros(18, dtype=np.float32)
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obs, reward, terminated, truncated, _ = env.step(dummy_action)
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total_reward += reward
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step_count += 1
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done = terminated or truncated
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time.sleep(1.0 / 60.0)
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comp_averages = env.get_reward_component_averages()
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print(f"\n--- Episode Stage: [{phase_enum.name}] ({label}) ---")
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print(f"Command Applied: vx={cmd[0]:.2f}, vy={cmd[1]:.2f}, yaw={cmd[2]:.2f}")
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print(f"Total Episode Reward: {total_reward:.4f}")
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print("Component Step Averages:")
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for name, value in comp_averages.items():
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print(f" • {name:<20}: {value:+.5f}")
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metrics = env.get_current_robot_metrics()
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dist = metrics[0]["distance_from_start"] if metrics else 0.0
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speed = metrics[0]["speed"] if metrics else 0.0
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avg_reward = total_reward / max(1, step_count)
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print(f" ├─ Average Reward / Step: {avg_reward:.4f}")
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print(f" ├─ Distance Travelled: {dist:.2f} m")
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print(f" ├─ Actual Avg Speed: {speed:.2f} m/s")
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print(f" └─ Steps Survived: {step_count} / {episode_length}")
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print("-" * 70)
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env.close()
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if __name__ == "__main__":
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evaluate_kinematics() |