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v0.1.10

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wty-yy
2025-12-18 23:14:18 +08:00
parent 1e1a04b4c0
commit 939dc69b7e
25 changed files with 411 additions and 50 deletions
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9
README.md
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@@ -28,9 +28,10 @@
| - | - | - |
| 电机动作执行随机延迟 | `action delay` | `<= RL控制间隔` |
| base负重 | `base mass` | `-1, 0, 1, 2, 3 kg` |
| 地面摩擦力 | `friction` | `0.4, 0.7, 1.0, 1.3, 1.6` |
#### 地形
1. 支持legged_gym中的部分地形, 包括: `wave, slope, rough_slope, stairs up, stairs down, obstacles, flat`, 除`flat`地形外其他地形可进行难度系数提升
1. 支持legged_gym中的部分地形, 包括: `wave, slope, stairs up, stairs down, obstacles, flat`, 除`flat`地形外其他地形可进行难度系数提升
2. 地面类型 (影响接触摩擦系数, 弹性摩擦系数), 包括: 橡胶地, 木地板, 瓷砖地
### 指标
@@ -41,8 +42,9 @@
| 1 | `dof_limits` | 关节超出软关节范围的大小 | 软关节范围阈值 | 总关节变化范围 | `1-x` |
| 2 | `lin_vel_err` | 线速度L2误差 | NA | 总线速度指令范围 | `1-x` |
| 3 | `ang_vel_err` | 角速度L2误差 | NA | 总角速度指令范围 | `1-x` |
| 4 | `base_height_std` | base高度变化方差 | NA | NA | `1-x` |
| 5 | `dof_power` | 电机耗能 | NA | 10 | `1-x` |
| 4 | `dof_power` | 电机耗能 | 缩放系数 | 100 | `1-x` |
| 5 | `orientation_stability` | 机身姿态稳定性 (Roll) | NA | NA | `1-x` |
| 6 | `torque_smoothness` | 力矩平滑度 | 缩放系数 | 30 | `1-x` |
### 速度追踪目标
针对在虚实迁移中发现的问题, 整理指标 (metrics) 内容如下:
@@ -58,6 +60,7 @@
总结速度最总目标 (goals) 如下:
| # | 目标名称 Goals | 描述 | reset条件 | 最大reset次数 |
| - | - | - | - | - |
| 1 | `max_velocity` | 单一维度的最大线/角速度 | 每次执行一个方向的指令, 再急停 | 6 |
| 2 | `diagonal_velocity` | 对角线速度变化 | 每次执行一对对角指令 | 8 |

7
UPDATE.md
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@@ -1,5 +1,12 @@
# UPDATE
TODO: 在模型崩溃时也记录下最后的gauge信息
## 20251218
### v0.1.10
1. 加入`--write-tensorboard`参数, 默认为`False`即不记录`gauge`的日志信息
2. 指令系数改为1.8 (比2.0稳定点)
3. 完成全部指标, 新增`dof_power, orientation_stability, torque_smoothness`
4. 加入雷达图绘图
Fix Bugs: 日志记录重复的问题
### v0.1.9
1. 在`MaxVelocityGoal`基础上加入`end_stance`, 最终保持站立姿态
2. 在开始goal控制前, 先等机器人落地, 通过线速度小于0.05阈值判断静止后, 执行goal

8
robogauge/scripts/run_eval_models.sh
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@@ -15,7 +15,7 @@ MODELS_FILE="$SCRIPT_DIR/evaluate_models.txt"
RUN_PY="$SCRIPT_DIR/run.py"
### Default Configure ###
EXP_NAME="go2_moe_flat" # Experiment name [-n]
EXP_NAME="" # Experiment name [-n]
TASK_NAME="go2_moe_flat" # Task name [-t]
SAVE_VIDEO=false # Whether to save video [-s]
@@ -53,12 +53,16 @@ if [ ${#models_paths[@]} -eq 0 ]; then
fi
### Run Evaluation Scripts ###
base_args="--task $TASK_NAME --headless --experiment-name $EXP_NAME"
base_args="--task $TASK_NAME --headless"
if [ "$SAVE_VIDEO" = true ]; then
base_args="$base_args --save-video"
fi
if [ -n "$EXP_NAME" ]; then
base_args="$base_args --exp-name $EXP_NAME"
fi
echo "================ Run Settings ================"
echo "Script Dir: $SCRIPT_DIR"
echo "Runner: $RUN_PY"

21
robogauge/tasks/custom/go2_flat_task.py
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@@ -1,3 +1,12 @@
# -*- coding: utf-8 -*-
'''
@File : go2_flat_task.py
@Time : 2025/12/18 20:19:25
@Author : wty-yy
@Version : 1.0
@Blog : https://wty-yy.github.io/
@Desc : Go2 Flat Task Configuration
'''
from robogauge.tasks.robots import Go2Config, Go2MoEConfig
from robogauge.tasks.gauge import FlatGaugeConfig
from robogauge.tasks.simulator.mujoco_config import MujocoConfig
@@ -22,15 +31,15 @@ class Go2FlatGaugeConfig(FlatGaugeConfig):
class Go2FlatConfig(Go2Config):
class commands(Go2Config.commands):
lin_vel_x = [-2.0, 2.0] # min max [m/s]
lin_vel_y = [-2.0, 2.0] # min max [m/s]
ang_vel_yaw = [-2.0, 2.0] # min max [rad/s]
lin_vel_x = [-1.8, 1.8] # min max [m/s]
lin_vel_y = [-1.8, 1.8] # min max [m/s]
ang_vel_yaw = [-1.8, 1.8] # min max [rad/s]
class Go2MoEFlatConfig(Go2MoEConfig):
class commands(Go2Config.commands):
lin_vel_x = [-2.0, 2.0] # min max [m/s]
lin_vel_y = [-2.0, 2.0] # min max [m/s]
ang_vel_yaw = [-2.0, 2.0] # min max [rad/s]
lin_vel_x = [-1.8, 1.8] # min max [m/s]
lin_vel_y = [-1.8, 1.8] # min max [m/s]
ang_vel_yaw = [-1.8, 1.8] # min max [rad/s]
class control(Go2Config.control):
# model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go2/go2_moe_cts_124k.pt"

8
robogauge/tasks/gauge/base_gauge.py
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@@ -26,7 +26,10 @@ from robogauge.tasks.gauge.goals import BaseGoal, MaxVelocityGoal, DiagonalVeloc
from robogauge.tasks.gauge.metrics import *
class BaseGauge:
def __init__(self, cfg: BaseGaugeConfig, robot_cfg: RobotConfig):
def __init__(self,
cfg: BaseGaugeConfig,
robot_cfg: RobotConfig,
):
self.cfg = cfg
self.robot_cfg = robot_cfg
self.goals_cfg = class_to_dict(self.cfg.goals)
@@ -79,7 +82,8 @@ class BaseGauge:
def create_new_goal_logger(self):
""" Create a new logger for new goal to metrics. """
if self.goal_idx >= len(self.goals): return
if self.goal_idx >= len(self.goals) or not self.cfg.write_tensorboard:
return
logger.create_tensorboard(
self.robot_cfg.robot_name,
Path(self.robot_cfg.control.model_path).stem,

14
robogauge/tasks/gauge/base_gauge_config.py
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@@ -11,6 +11,7 @@ from robogauge.utils.config import Config
class BaseGaugeConfig(Config):
gauge_class = 'BaseGauge'
write_tensorboard = False # Whether to write tensorboard logs
class assets:
terrain_xml = '{ROBOGAUGE_ROOT_DIR}/resources/terrains/flat.xml'
@@ -34,7 +35,7 @@ class BaseGaugeConfig(Config):
class visualization:
enabled = True
dof_force = True
dof_torque = True
dof_pos = True
class lin_vel_err:
@@ -42,3 +43,14 @@ class BaseGaugeConfig(Config):
class ang_vel_err:
enabled = True
class dof_power:
enabled = True
scaling_factor = 100.0 # [W] scaling factor for power metric
class orientation_stability:
enabled = True
class torque_smoothness:
enabled = True
scaling_factor = 30.0 # [Nm] scaling factor for torque smoothness metric

2
robogauge/tasks/gauge/gauge_configs/flat_gauge_config.py
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@@ -36,7 +36,7 @@ class FlatGaugeConfig(BaseGaugeConfig):
class visualization:
enabled = True
dof_force = True
dof_torque = True
dof_pos = True
class lin_vel_err:

3
robogauge/tasks/gauge/metrics/__init__.py
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@@ -1,4 +1,5 @@
from .base_metric import BaseMetric
from .dof_metrics import DofLimitsMetric
from .dof_metrics import DofLimitsMetric, DofPowerMetric
from .visualization import VisualizationMetric
from .vel_metrics import LinVelErrMetric, AngVelErrMetric
from .stable_metric import OrientationStabilityMetric, TorqueSmoothnessMetric

12
robogauge/tasks/gauge/metrics/base_metric.py
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@@ -1,3 +1,12 @@
# -*- coding: utf-8 -*-
'''
@File : base_metric.py
@Time : 2025/12/18 20:18:45
@Author : wty-yy
@Version : 1.0
@Blog : https://wty-yy.github.io/
@Desc : Base Metric Implementation
'''
from robogauge.utils.logger import logger
from robogauge.tasks.robots import RobotConfig
from robogauge.tasks.simulator.sim_data import SimData
@@ -10,6 +19,9 @@ class BaseMetric:
def __init__(self, robot_cfg: RobotConfig, **kwargs):
self.robot_cfg = robot_cfg
def reset(self):
pass
def __call__(self, sim_data: SimData, goal_data: GoalData) -> float:
value = 0.0
logger.log(value, self.name, step=sim_data.n_step)

35
robogauge/tasks/gauge/metrics/dof_metrics.py
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@@ -1,3 +1,12 @@
# -*- coding: utf-8 -*-
'''
@File : dof_metrics.py
@Time : 2025/12/18 20:18:24
@Author : wty-yy
@Version : 1.0
@Blog : https://wty-yy.github.io/
@Desc : DOF Limits Metric Implementation
'''
import numpy as np
from robogauge.tasks.robots import RobotConfig
@@ -47,3 +56,29 @@ class DofLimitsMetric(BaseMetric):
rms_value = 1 - np.sqrt(np.mean(np.square(values)))
logger.log(1 - rms_value, f'dof_limits/rms', step=sim_data.n_step)
return rms_value
class DofPowerMetric(BaseMetric):
""" Metric to log DOF power efficiency. """
name = 'dof_power_metric'
def __init__(self,
robot_cfg: RobotConfig,
scaling_factor: float = 100.0,
**kwargs
):
super().__init__(robot_cfg)
self.scaling_factor = scaling_factor
def __call__(self, sim_data: SimData, goal_data: GoalData) -> float:
values = []
for i in range(len(sim_data.proprio.joint.torque)):
torque = sim_data.proprio.joint.torque[i]
velocity = sim_data.proprio.joint.vel[i]
power = abs(torque * velocity)
values.append(power)
dof_name = sim_data.proprio.joint.names[i]
logger.log(power, f'dof_power/{dof_name}', step=sim_data.n_step)
rms_power = np.sqrt(np.mean(np.square(values)))
metric_power = 1 - rms_power / self.scaling_factor
logger.log(rms_power, f'dof_power/rms', step=sim_data.n_step)
return metric_power

61
robogauge/tasks/gauge/metrics/stable_metric.py Normal file
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@@ -0,0 +1,61 @@
# -*- coding: utf-8 -*-
'''
@File : height_metric.py
@Time : 2025/12/18 20:18:33
@Author : wty-yy
@Version : 1.0
@Blog : https://wty-yy.github.io/
@Desc : Orientation Stability, Torque Smoothness Metric Implementation
'''
import numpy as np
from robogauge.tasks.robots import RobotConfig
from robogauge.tasks.gauge.metrics.base_metric import BaseMetric, GoalData, SimData
from robogauge.utils.math_utils import get_projected_gravity
from robogauge.utils.logger import logger
class OrientationStabilityMetric(BaseMetric):
""" Metric to log height stability. """
name = 'height_std_metric'
def __init__(self,
robot_cfg: RobotConfig,
**kwargs
):
super().__init__(robot_cfg)
def __call__(self, sim_data: SimData, goal_data: GoalData) -> float:
projected_gravity = get_projected_gravity(sim_data.proprio.base.quat)
projected_x = projected_gravity[0]
metric_value = 1 - abs(projected_x) # consider roll only
logger.log(abs(projected_x), f'stable_metric/projected_x_abs', step=sim_data.n_step)
return metric_value
class TorqueSmoothnessMetric(BaseMetric):
""" Metric to log torque smoothness. """
name = 'torque_smoothness_metric'
def __init__(self,
robot_cfg: RobotConfig,
scaling_factor: float = 30.0,
**kwargs
):
super().__init__(robot_cfg)
self.last_torque = None
self.scaling_factor = scaling_factor
def reset(self):
self.last_torque = None
def __call__(self, sim_data: SimData, goal_data: GoalData) -> float:
current_torque = np.array(sim_data.proprio.joint.torque, np.float32)
if self.last_torque is None:
self.last_torque = current_torque
return 1.0 # No change at first step
torque_diff = current_torque - self.last_torque
rms_value = np.sqrt(np.mean(np.square(torque_diff)))
metric_value = 1.0 - rms_value / self.scaling_factor
logger.log(rms_value, f'stable_metric/torque_rms_diff', step=sim_data.n_step)
return metric_value

9
robogauge/tasks/gauge/metrics/vel_metrics.py
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@@ -1,3 +1,12 @@
# -*- coding: utf-8 -*-
'''
@File : vel_metrics.py
@Time : 2025/12/18 20:18:56
@Author : wty-yy
@Version : 1.0
@Blog : https://wty-yy.github.io/
@Desc : Velocity Metrics Implementation
'''
import numpy as np
from robogauge.tasks.robots import RobotConfig

21
robogauge/tasks/gauge/metrics/visualization.py
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@@ -1,3 +1,12 @@
# -*- coding: utf-8 -*-
'''
@File : visualization.py
@Time : 2025/12/18 20:19:09
@Author : wty-yy
@Version : 1.0
@Blog : https://wty-yy.github.io/
@Desc : Visualization Metric Implementation
'''
from robogauge.tasks.robots import RobotConfig
from robogauge.tasks.gauge.metrics.base_metric import BaseMetric, SimData, GoalData
@@ -9,20 +18,20 @@ class VisualizationMetric(BaseMetric):
def __init__(self,
robot_cfg: RobotConfig,
dof_force: bool = False,
dof_torque: bool = False,
dof_pos: bool = False,
**kwargs
):
super().__init__(robot_cfg)
self.dof_force = dof_force
self.dof_torque = dof_torque
self.dof_pos = dof_pos
def __call__(self, sim_data: SimData, goal_data: GoalData) -> float:
for i in range(len(sim_data.proprio.joint.force)):
for i in range(len(sim_data.proprio.joint.torque)):
name = sim_data.proprio.joint.names[i]
if self.dof_force:
force = sim_data.proprio.joint.force[i]
logger.log(force, f'dof_force/{name}', step=sim_data.n_step)
if self.dof_torque:
torque = sim_data.proprio.joint.torque[i]
logger.log(torque, f'dof_torque/{name}', step=sim_data.n_step)
if self.dof_pos:
pos = sim_data.proprio.joint.pos[i]
logger.log(pos, f'dof_pos/{name}', step=sim_data.n_step)

3
robogauge/tasks/pipeline/base_pipeline.py
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@@ -100,6 +100,9 @@ class BasePipeline:
first_reset = True
self.last_reset_time = sim_data.sim_time
sim_data = self.sim.step()
except Exception as e:
logger.error(f"❌ Pipeline execution failed with error: {e}")
raise e
finally:
self.sim.close_viewer()
self.sim.close_video_writer()

2
robogauge/tasks/pipeline/multi_pipeline.py
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@@ -144,7 +144,7 @@ class MultiPipeline:
save_path = logger.log_dir / "aggregated_results.yaml"
with open(save_path, 'w') as file:
yaml.dump(summary, file, allow_unicode=True)
yaml.dump(summary, file, allow_unicode=True, sort_keys=False)
logger.info("✅ Aggregated execution finished.")
logger.info(f"📁 Aggregated results saved to: {save_path}")

16
robogauge/tasks/robots/base_robot.py
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@@ -45,19 +45,3 @@ class BaseRobot:
action = np.zeros(self.num_action, dtype=np.float32)
return action, self.p_gains, self.d_gains, self.control_type
def get_projected_gravity(quat):
""" Compute world frame gravity (0, 0, -1) projected into robot base frame.
Args:
quat: (4,) quaternion (w, x, y, z) from robot base to world frame
Returns:
projected_gravity: (3,) projected gravity vector in robot base frame
"""
qw, qx, qy, qz = quat
gravity_orientation = np.zeros(3)
gravity_orientation[0] = 2 * (-qz * qx + qw * qy)
gravity_orientation[1] = -2 * (qz * qy + qw * qx)
gravity_orientation[2] = 1 - 2 * (qw * qw + qz * qz)
return gravity_orientation

3
robogauge/tasks/robots/go2/go2.py
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@@ -10,7 +10,8 @@
import torch
import numpy as np
from robogauge.tasks.robots.base_robot import BaseRobot, get_projected_gravity
from robogauge.tasks.robots.base_robot import BaseRobot
from robogauge.utils.math_utils import get_projected_gravity
from robogauge.tasks.robots.go2.go2_config import Go2Config
from robogauge.tasks.simulator.sim_data import SimData
from robogauge.tasks.gauge.goal_data import GoalData

5
robogauge/tasks/robots/go2/go2_moe.py
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@@ -10,12 +10,7 @@
import torch
import numpy as np
from robogauge.tasks.robots.base_robot import BaseRobot, get_projected_gravity
from robogauge.tasks.robots.go2.go2_config import Go2Config
from robogauge.tasks.robots.go2.go2 import Go2
from robogauge.tasks.simulator.sim_data import SimData
from robogauge.tasks.gauge.goal_data import GoalData
from robogauge.utils.logger import logger
class Go2MoE(Go2):
def get_action(self, obs: np.ndarray):

4
robogauge/tasks/simulator/mujoco_simulator.py
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@@ -200,7 +200,7 @@ class MujocoSimulator:
joint=JointState(
pos=self.get_sensor_data('joint_pos'),
vel=self.get_sensor_data('joint_vel'),
force=self.get_sensor_data('joint_eff'),
torque=self.get_sensor_data('joint_eff'),
limits=self.dof_limits,
names=self.dof_names,
),
@@ -389,7 +389,7 @@ class MujocoSimulator:
logger.info("Proprioception shapes:")
logger.info(f" joint.pos: { _shape(jp.pos) }")
logger.info(f" joint.vel: { _shape(jp.vel) }")
logger.info(f" joint.force: { _shape(jp.force) }")
logger.info(f" joint.torque: { _shape(jp.torque) }")
logger.info(f" base.pos: { _shape(bs.pos) }")
logger.info(f" base.quat: { _shape(bs.quat) }")

2
robogauge/tasks/simulator/sim_data.py
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@@ -5,7 +5,7 @@ from dataclasses import dataclass
class JointState:
pos: np.ndarray # [rad] shape (n_dof,)
vel: np.ndarray # [rad/s] shape (n_dof,)
force: np.ndarray # [N*m] shape (n_dof,)
torque: np.ndarray # [N*m] shape (n_dof,)
limits: np.ndarray # [rad] shape (n_dof, 2), lower and upper limits
names: list # list of joint names

2
robogauge/utils/helpers.py
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@@ -71,6 +71,8 @@ def parse_args():
{"name": "--headless", "action": "store_true", "default": False, "help": "Run in headless mode."},
{"name": "--save-video", "action": "store_true", "default": False, "help": "Save video output."},
{"name": "--seed", "type": int, "default": 42, "help": "Random seed."},
{"name": "--write-tensorboard", "action": "store_true", "default": False, "help": "Write tensorboard logs."},
{"name": "--plot-radar", "action": "store_true", "default": False, "help": "Plot radar charts for metrics."},
# Multiprocessing parameters, with different seeds
{"name": "--multi", "action": "store_true", "default": False, "help": "Enable multiprocessing."},

11
robogauge/utils/logger.py
View File

@@ -76,6 +76,13 @@ class Logger:
self.logger = logging.getLogger(experiment_name + "_logger")
self.logger.setLevel(log_level)
self.logger.propagate = False
# Clear existing handlers to prevent duplicate logging
if self.logger.hasHandlers():
for handler in self.logger.handlers[:]:
handler.close()
self.logger.removeHandler(handler)
self.time_tag = time.strftime("%Y%m%d-%H-%M-%S")
self.tag = f"{self.time_tag}_{run_name}"
self.experiment_name = experiment_name
@@ -141,8 +148,8 @@ class Logger:
"""
if self.writer is not None:
self.writer.add_scalar(tag, value, step)
else:
self.warning("Tensorboard writer is not initialized, skipping log.")
# else:
# self.warning("Tensorboard writer is not initialized, skipping log.")
logger = Logger()

18
robogauge/utils/math_utils.py Normal file
View File

@@ -0,0 +1,18 @@
import numpy as np
def get_projected_gravity(quat):
""" Compute world frame gravity (0, 0, -1) projected into robot base frame.
Args:
quat: (4,) quaternion (w, x, y, z) from robot base to world frame
Returns:
projected_gravity: (3,) projected gravity vector in robot base frame
"""
qw, qx, qy, qz = quat
gravity_orientation = np.zeros(3)
gravity_orientation[0] = 2 * (-qz * qx + qw * qy)
gravity_orientation[1] = -2 * (qz * qy + qw * qx)
gravity_orientation[2] = 1 - 2 * (qw * qw + qz * qz)
return gravity_orientation

183
robogauge/utils/radar_plot.py Normal file
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@@ -0,0 +1,183 @@
"""
python robogauge/utils/radar_plot.py \
/home/xfy/Coding/robot_gauge/logs/go2_moe_flat_debug_multi/20251218-22-49-29_run_multi/aggregated_results.yaml \
/home/xfy/Coding/robot_gauge/logs/go2_flat_debug_multi/20251218-22-59-04_run_multi/aggregated_results.yaml \
--out logs/go2_flat_vs_moe_flat.png
"""
import matplotlib.pyplot as plt
config = {
"font.family": 'serif', # 衬线字体
"figure.figsize": (6, 6), # 图像大小
"font.size": 14, # 字号大小
"mathtext.fontset": 'cm', # 渲染数学公式字体
'axes.unicode_minus': False # 显示负号
}
plt.rcParams.update(config)
import numpy as np
import yaml
import argparse
import os
import sys
# 设置字体，尝试匹配参考图的衬线体风格 (如果系统没有会回退到默认)
plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.serif'] = ['Times New Roman', 'DejaVu Serif', 'serif']
def parse_value_string(val_str):
if isinstance(val_str, (int, float)):
return float(val_str)
if isinstance(val_str, str):
if '±' in val_str:
return float(val_str.split('±')[0].strip())
return float(val_str)
return 0.0
def load_data(file_paths):
all_data = []
# 指标键名
metric_keys = [
'lin_vel_err',
'ang_vel_err',
'orientation_stability',
'dof_limits',
'torque_smoothness',
'dof_power'
]
# 标签 (增加换行以避免拥挤)
labels_map = {
'lin_vel_err': 'Lin Vel\nAccuracy',
'ang_vel_err': 'Ang Vel\nAccuracy',
'dof_limits': 'Joint Limits\nMargin',
'dof_power': 'Energy\nEfficiency',
'orientation_stability': 'Orientation\nStability',
'torque_smoothness': 'Torque\nSmoothness',
}
for path in file_paths:
if not os.path.exists(path):
continue
with open(path, 'r', encoding='utf-8') as f:
content = yaml.safe_load(f)
raw_path = content.get('model_path', 'Unknown_Model')
# 简化图例名称：只取文件名，去掉 .pt
model_name = os.path.basename(raw_path).replace('.pt', '')
# 如果名称过长，可以考虑进一步截断，例如：
# if len(model_name) > 20: model_name = model_name[:10] + "..." + model_name[-5:]
values = []
for k in metric_keys:
if k in content:
raw_val = content[k]['mean']
values.append(parse_value_string(raw_val))
else:
values.append(0.0)
all_data.append({'name': model_name, 'values': values})
return all_data, [labels_map[k] for k in metric_keys]
def plot_radar(data_list, labels, output_file=None):
if not data_list:
print("No data to plot.")
return
num_vars = len(labels)
angles = np.linspace(0, 2 * np.pi, num_vars, endpoint=False).tolist()
angles += angles[:1] # 闭合
# --- 颜色设置 ---
# 使用参考图类似的配色 (深蓝、浅蓝、绿等)
# 或者使用 'tab10', 'Set2' 等
colors = plt.cm.get_cmap("tab10", len(data_list))
# 创建画布，稍微宽一点以便放图例
fig, ax = plt.subplots(figsize=(10, 8), subplot_kw=dict(polar=True))
# --- 核心修改：调整布局 ---
# left=0.1, bottom=0.1, top=0.9 是为了给标题留空
# right=0.75 是关键！这意味着图表只占画布左边 75% 的宽度，右边 25% 留给图例
plt.subplots_adjust(left=0.05, right=0.75, top=0.9, bottom=0.1)
# 设置方向
ax.set_theta_offset(np.pi / 2)
ax.set_theta_direction(-1)
# --- 绘制标签 ---
plt.xticks(angles[:-1], labels, color='#444444', size=13)
# 标签对齐优化
for label, angle in zip(ax.get_xticklabels(), angles[:-1]):
if angle in (0, np.pi):
label.set_horizontalalignment('center')
elif 0 < angle < np.pi:
label.set_horizontalalignment('left')
else:
label.set_horizontalalignment('right')
# --- 绘制刻度 ---
ax.set_rlabel_position(0)
# 字体稍微调淡一点，不要抢眼
plt.yticks([0.25, 0.50, 0.75, 1.00], ["0.25", "0.50", "0.75", "1.00"],
color="grey", size=10)
plt.ylim(0, 1.05)
# 网格线：点状虚线，稍微粗一点
ax.grid(True, color='gray', linestyle=':', linewidth=1.5, alpha=0.5)
ax.spines['polar'].set_visible(False)
# --- 绘制数据 ---
# 加粗线条以匹配 bsuite 风格
linewidth = 3.0
for idx, item in enumerate(data_list):
values = item['values']
name = item['name']
values_closed = values + values[:1]
color = colors(idx)
ax.plot(angles, values_closed, linewidth=linewidth, linestyle='-', label=name, color=color)
ax.fill(angles, values_closed, color=color, alpha=0.2) # 填充透明度低一点
# --- 核心修改：图例位置 ---
# bbox_to_anchor=(1.1, 0.2) 的意思是：
# 锚点位于坐标轴右侧(1.1倍宽位置)，垂直方向在底部(0.2倍高位置)
# loc='upper left' 意思是图例的左上角对齐这个锚点
legend = plt.legend(
loc='upper left',
bbox_to_anchor=(1.1, 0.3), # 调整这里的 0.3 可以上下移动图例
title="Models",
title_fontsize=16,
fontsize=12,
frameon=False, # 无边框
labelspacing=0.8 # 图例行间距
)
# 设置图例标题对齐方式 (左对齐)
legend._legend_box.align = "left"
plt.title('Multi-Model Performance Comparison', size=18, y=1.08, color='#333333')
if output_file:
plt.savefig(output_file, dpi=300, bbox_inches='tight') # bbox_inches='tight' 会自动裁剪白边
print(f"Plot saved to {output_file}")
else:
plt.show()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('files', metavar='F', type=str, nargs='+', help='YAML files')
parser.add_argument('--out', type=str, default=None, help='Output file')
# 调试用（如果你直接运行脚本，请取消注释并填入你的文件名）
# sys.argv = ['plot.py', 'aggregated_results.yaml', 'aggregated_results2.yaml', '--out', 'fixed_radar.png']
args = parser.parse_args()
data, metrics_labels = load_data(args.files)
plot_radar(data, metrics_labels, output_file=args.out)

2
robogauge/utils/task_register.py
View File

@@ -63,6 +63,8 @@ class TaskRegister():
sim_cfg.viewer.headless = args.headless
if args.save_video is not None:
sim_cfg.render.save_video = args.save_video
if args.write_tensorboard is not None:
gauger_cfg.write_tensorboard = args.write_tensorboard
if hasattr(args, 'friction') and args.friction is not None:
sim_cfg.domain_rand.friction = args.friction
if hasattr(args, 'base_mass') and args.base_mass is not None: