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v1.1.0; fix metrics bugs

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wty-yy
2026-01-10 02:11:44 +08:00
parent 0f2dc29dfc
commit a82f3d8930
10 changed files with 31 additions and 14 deletions
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13
robogauge/tasks/gauge/metrics/dof_metrics.py
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@@ -35,8 +35,12 @@ class DofLimitsMetric(BaseMetric):
lower_limit = sim_data.proprio.joint.limits[i, 0]
upper_limit = sim_data.proprio.joint.limits[i, 1]
dof_range = upper_limit - lower_limit
soft_lower_limit = lower_limit + (1 - self.soft_dof_limit_ratio) * dof_range
soft_upper_limit = upper_limit - (1 - self.soft_dof_limit_ratio) * dof_range
if dof_range <= 1e-6:
logger.warning(f"DOF range for {sim_data.proprio.joint.names[i]} is too small ({dof_range:.6f}), skipping metric calculation.")
continue
soft_lower_limit = lower_limit + (1 - self.soft_dof_limit_ratio) * dof_range / 2
soft_upper_limit = upper_limit - (1 - self.soft_dof_limit_ratio) * dof_range / 2
pos = sim_data.proprio.joint.pos[i]
dof_name = sim_data.proprio.joint.names[i]
@@ -53,6 +57,11 @@ class DofLimitsMetric(BaseMetric):
values.append(value)
else:
values.append(value)
if len(values) == 0:
logger.warning("No DOF limit values calculated, returning 0.0.")
return 0.0
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

7
robogauge/tasks/gauge/metrics/stable_metric.py
View File

@@ -28,9 +28,9 @@ class OrientationStabilityMetric(BaseMetric):
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)
projected_y = projected_gravity[1]
metric_value = 1 - abs(projected_y) # consider roll only
logger.log(abs(projected_y), f'stable_metric/projected_y_abs', step=sim_data.n_step)
return metric_value
class TorqueSmoothnessMetric(BaseMetric):
@@ -55,6 +55,7 @@ class TorqueSmoothnessMetric(BaseMetric):
self.last_torque = current_torque
return 1.0 # No change at first step
torque_diff = current_torque - self.last_torque
self.last_torque = current_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)