import numpy as np from robogauge.tasks.robots import RobotConfig from robogauge.tasks.simulator.sim_data import SimData from robogauge.utils.logger import logger def example_metric( sim_data: SimData, robot_cfg: RobotConfig, **kwargs ) -> float: """ An example metric function. """ value = 0.0 # Compute some metric value based on sim_data and robot_cfg logger.log(value, 'example_metric', step=sim_data.n_step) return value def dof_limits_metric( sim_data: SimData, robot_cfg: RobotConfig, soft_dof_limit_ratio: float = 0.9, dof_names: list = None, **kwargs ) -> float: """ Metric to log DOF limit violations. """ values = [] for i in range(len(sim_data.proprio.joint.limits)): 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 - soft_dof_limit_ratio) * dof_range soft_upper_limit = upper_limit - (1 - soft_dof_limit_ratio) * dof_range pos = sim_data.proprio.joint.pos[i] dof_name = sim_data.proprio.joint.names[i] value = 0 if pos < soft_lower_limit: value = soft_lower_limit - pos elif pos > soft_upper_limit: value = pos - soft_upper_limit value /= dof_range # Normalize by DOF range logger.log(value, f'dof_limits/{dof_name}', step=sim_data.n_step) if dof_names is not None: for use_name in dof_names: if use_name in dof_name: values.append(value) else: values.append(value) 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 def visualization_metric( sim_data: SimData, robot_cfg: RobotConfig, dof_force: bool = False, dof_pos: bool = False, **kwargs, ): """ Metric to visualize various robot states in the simulator. """ for i in range(len(sim_data.proprio.joint.force)): name = sim_data.proprio.joint.names[i] if dof_force: force = sim_data.proprio.joint.force[i] logger.log(force, f'dof_force/{name}', step=sim_data.n_step) if dof_pos: pos = sim_data.proprio.joint.pos[i] logger.log(pos, f'dof_pos/{name}', step=sim_data.n_step) return 0.0