diff --git a/baselines/x-navdp/README.md b/baselines/x-navdp/README.md index 058361b..951eea8 100644 --- a/baselines/x-navdp/README.md +++ b/baselines/x-navdp/README.md @@ -207,7 +207,7 @@ Run point-goal evaluation: ```bash bash eval/scripts/run_evaluation.sh \ - --config_file eval/config/eval_pointgoal/quadruped_clutter_easy.yaml + --config_file eval/config/eval_pointgoal/quadruped_internscene_commercial.yaml ``` By default, evaluation runs all start-goal samples in the selected scene. Use `--num_episodes` to evaluate a subset and `--max_steps` to cap the total simulation steps for smoke tests or debugging. diff --git a/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_easy.yaml b/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_easy.yaml index ef7466d..3f12d2c 100644 --- a/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_easy.yaml +++ b/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_easy.yaml @@ -1,4 +1,4 @@ -run_id: default +run_id: pointgoal_humanoid_eval_clutter_easy run_root_dir: outputs/evaluation logger: null @@ -7,10 +7,10 @@ environment: task_type: pointgoal scene_dir: data/scenes/cluttered_easy scene_index: 0 - num_envs: 4 + num_envs: 1 rgb_history_window: 1024 depth_history_window: 1 - rgb_num_samples: 8 + rgb_num_samples: 7 depth_num_samples: 1 rgb_image_size: 224 depth_image_size: 224 @@ -43,9 +43,9 @@ obs_mapping: robot_quat: robot_rot mpc: - N: 30 # Prediction horizon + N: 75 # Prediction horizon desired_v: 0.5 # Desired velocity v_max: 0.5 # Maximum velocity w_max: 0.5 # Maximum angular velocity ref_gap: 3 # Reference gap - T: 0.1 # Time step + T: 0.04 # Time step diff --git a/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_hard.yaml b/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_hard.yaml index b8513a5..d90e370 100644 --- a/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_hard.yaml +++ b/baselines/x-navdp/eval/config/eval_pointgoal/humanoid_clutter_hard.yaml @@ -1,4 +1,4 @@ -run_id: default +run_id: pointgoal_humanoid_eval_clutter_hard run_root_dir: outputs/evaluation logger: null @@ -7,10 +7,10 @@ environment: task_type: pointgoal scene_dir: data/scenes/cluttered_hard scene_index: 0 - num_envs: 4 + num_envs: 1 rgb_history_window: 1024 depth_history_window: 1 - rgb_num_samples: 8 + rgb_num_samples: 7 depth_num_samples: 1 rgb_image_size: 224 depth_image_size: 224 @@ -43,9 +43,9 @@ obs_mapping: robot_quat: robot_rot mpc: - N: 30 # Prediction horizon + N: 75 # Prediction horizon desired_v: 0.5 # Desired velocity v_max: 0.5 # Maximum velocity w_max: 0.5 # Maximum angular velocity ref_gap: 3 # Reference gap - T: 0.1 # Time step + T: 0.04 # Time step diff --git a/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_easy.yaml b/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_easy.yaml index f7bed77..08709d0 100644 --- a/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_easy.yaml +++ b/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_easy.yaml @@ -1,4 +1,4 @@ -run_id: default +run_id: pointgoal_quadruped_eval_clutter_easy run_root_dir: outputs/evaluation logger: null @@ -7,14 +7,14 @@ environment: task_type: pointgoal scene_dir: data/scenes/cluttered_easy scene_index: 0 - num_envs: 4 + num_envs: 1 rgb_history_window: 1024 depth_history_window: 1 - rgb_num_samples: 8 + rgb_num_samples: 7 depth_num_samples: 1 rgb_image_size: 224 depth_image_size: 224 - height_offset: 0.2 + height_offset: 0.4 stuck_window_size: 50 stuck_threshold: 0.1 arrival_threshold: 1.0 @@ -43,9 +43,9 @@ obs_mapping: robot_quat: robot_rot mpc: - N: 30 # Prediction horizon + N: 75 # Prediction horizon desired_v: 0.5 # Desired velocity v_max: 0.5 # Maximum velocity w_max: 0.5 # Maximum angular velocity ref_gap: 3 # Reference gap - T: 0.1 # Time step + T: 0.04 # Time step diff --git a/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_hard.yaml b/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_hard.yaml index 8c82340..1f4445e 100644 --- a/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_hard.yaml +++ b/baselines/x-navdp/eval/config/eval_pointgoal/quadruped_clutter_hard.yaml @@ -1,4 +1,4 @@ -run_id: default +run_id: pointgoal_quadruped_eval_clutter_hard run_root_dir: outputs/evaluation logger: null @@ -7,14 +7,14 @@ environment: task_type: pointgoal scene_dir: data/scenes/cluttered_hard scene_index: 0 - num_envs: 4 + num_envs: 1 rgb_history_window: 1024 depth_history_window: 1 - rgb_num_samples: 8 + rgb_num_samples: 7 depth_num_samples: 1 rgb_image_size: 224 depth_image_size: 224 - height_offset: 0.2 + height_offset: 0.4 stuck_window_size: 50 stuck_threshold: 0.1 arrival_threshold: 1.0 @@ -43,9 +43,9 @@ obs_mapping: robot_quat: robot_rot mpc: - N: 30 # Prediction horizon + N: 75 # Prediction horizon desired_v: 0.5 # Desired velocity v_max: 0.5 # Maximum velocity w_max: 0.5 # Maximum angular velocity ref_gap: 3 # Reference gap - T: 0.1 # Time step + T: 0.04 # Time step diff --git a/baselines/x-navdp/eval/scripts/run_evaluation.sh b/baselines/x-navdp/eval/scripts/run_evaluation.sh index 008f57d..a8f30c5 100644 --- a/baselines/x-navdp/eval/scripts/run_evaluation.sh +++ b/baselines/x-navdp/eval/scripts/run_evaluation.sh @@ -45,7 +45,7 @@ done if [ -z "$CONFIG_FILE" ]; then echo "Error: --config_file is required" - echo "Usage: bash scripts/run_evaluation.sh --config_file eval/config/eval_pointgoal/quadruped_clutter_easy.yaml" + echo "Usage: bash scripts/run_evaluation.sh --config_file eval/config/eval_pointgoal/quadruped_internscene_commercial.yaml" exit 1 fi diff --git a/baselines/x-navdp/src/environment/tasks/event_utils.py b/baselines/x-navdp/src/environment/tasks/event_utils.py index 5b462d1..d95bd85 100644 --- a/baselines/x-navdp/src/environment/tasks/event_utils.py +++ b/baselines/x-navdp/src/environment/tasks/event_utils.py @@ -320,9 +320,9 @@ def pointnav_reset_eval(env: ManagerBasedEnv, if global_occ_path is not None: global _occ_cache_path, _occ_cache_data if _occ_cache_path != global_occ_path: - _gs = 0.1 * scale * scale_factor + _gs = 0.1 * scale_factor occ_pcd = o3d.io.read_point_cloud(global_occ_path) - occ_point = np.array(occ_pcd.points) * scale * scale_factor + occ_point = np.array(occ_pcd.points) * scale_factor _occ_min, _occ_max = occ_point.min(axis=0), occ_point.max(axis=0) grid_dimension = np.ceil((_occ_max[0:2] - _occ_min[0:2]) / _gs).astype(int) decision_map = np.zeros(grid_dimension, dtype=np.int32) @@ -363,7 +363,7 @@ def pointnav_reset_eval(env: ManagerBasedEnv, for i in range(env_ids.shape[0]): idx = int(count % sample_points.shape[0]) start_goal_pair = sample_points[idx].copy() - start_goal_pair[:4] = start_goal_pair[:4] * scale + start_goal_pair[:4] = start_goal_pair[:4] * scale_factor start_points = np.array([start_goal_pair[0], start_goal_pair[1], 0]) goal_points = np.array([start_goal_pair[2], start_goal_pair[3], 0])