144 lines
5.9 KiB
Python
144 lines
5.9 KiB
Python
# -*- coding: utf-8 -*-
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'''
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@File : base_pipeline.py
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@Time : 2025/11/27 15:53:26
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@Author : wty-yy
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@Version : 1.0
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@Blog : https://wty-yy.github.io/
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@Desc : Base Pipeline for Robogauge
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'''
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import yaml
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import random
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import traceback
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import numpy as np
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from pathlib import Path
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from copy import deepcopy
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from robogauge.utils.logger import logger
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from robogauge.tasks.simulator import MujocoSimulator, MujocoConfig, SimData
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from robogauge.tasks.robots import (
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BaseRobot, RobotConfig, Go2Config, Go2, Go2MoEConfig, Go2MoE
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)
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from robogauge.tasks.gauge import BaseGauge, BaseGaugeConfig
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from robogauge.tasks.gauge.goal_data import GoalData, VelocityGoal, PositionGoal
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from robogauge.utils.helpers import class_to_dict
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class BasePipeline:
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def __init__(self,
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run_name: str,
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simulator_cfg: MujocoConfig,
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robot_cfg: RobotConfig,
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gauge_cfg: BaseGaugeConfig
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):
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self.run_name = run_name
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self.sim_cfg = simulator_cfg
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self.robot_cfg = robot_cfg
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self.gauge_cfg = gauge_cfg
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self.sim: MujocoSimulator = eval(simulator_cfg.simulator_class)(simulator_cfg)
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self.robot: BaseRobot = eval(robot_cfg.robot_class)(robot_cfg)
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self.gauge: BaseGauge = eval(gauge_cfg.gauge_class)(gauge_cfg, robot_cfg)
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self.first_reset = True
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self.last_reset_time = 0.0
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# save configs
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cfg = {}
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for name in ['sim_cfg', 'robot_cfg', 'gauge_cfg']:
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obj = getattr(self, name)
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obj_dict = class_to_dict(obj)
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cfg.update({name: obj_dict})
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with open(Path(logger.log_dir) / "configs.yaml", 'w') as file:
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yaml.dump(cfg, file)
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def load(self):
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self.sim.load(
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self.gauge_cfg.assets.terrain_xml,
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self.robot_cfg.assets.robot_xml,
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self.gauge_cfg.assets.terrain_spawn_pos,
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self.robot_cfg.control.default_dof_pos
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)
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def run(self):
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logger.info(f"🚀 Starting single run: {self.run_name}")
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try:
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self.load()
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sim_data = self.sim.step()
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frame_skip = int(self.robot_cfg.control.control_dt / self.sim_cfg.physics.simulation_dt)
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assert frame_skip * self.sim_cfg.physics.simulation_dt == self.robot_cfg.control.control_dt, \
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"Control dt must be multiple of simulation dt."
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logger.info(f"Sim FPS: {1.0 / self.sim_cfg.physics.simulation_dt:.2f}, Control FPS: {1.0 / self.robot_cfg.control.control_dt:.2f}, Frame Skip: {frame_skip:d}")
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logger.info("Running pipeline...")
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while not self.gauge.is_done():
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if self.first_reset: # wait for robot to be still
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goal_data = GoalData(
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goal_type=self.robot_cfg.control.support_goal,
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velocity_goal=VelocityGoal(), # zero velocity
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position_goal=PositionGoal(), # current position
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)
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if np.linalg.norm(sim_data.proprio.base.lin_vel) < 0.05 and sim_data.sim_time - self.last_reset_time > 0.1:
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self.first_reset = False
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else:
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goal_data = self.gauge.get_goal(sim_data)
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if goal_data is None: # Change goal
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sim_data = self.reset_sim(sim_data)
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continue
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if goal_data.visualization_pos is not None:
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self.sim.set_target_pos(goal_data.visualization_pos)
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else:
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self.sim.set_target_pos(None)
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obs = self.robot.build_observation(self.add_noise(sim_data), goal_data)
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action, p_gains, d_gains, control_type = self.robot.get_action(obs)
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if self.sim_cfg.domain_rand.action_delay:
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actions_start_decimation = random.randint(0, frame_skip)
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else:
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self.sim.setup_action(action, p_gains, d_gains, control_type)
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for i in range(frame_skip):
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if self.sim_cfg.domain_rand.action_delay and i == actions_start_decimation:
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self.sim.setup_action(action, p_gains, d_gains, control_type)
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sim_data = self.sim.step()
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self.gauge.update_metrics(sim_data, goal_data)
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if self.gauge.is_reset(sim_data):
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sim_data = self.reset_sim(sim_data)
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except Exception as e:
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logger.error(f"❌ Pipeline execution failed with error: {e},\n{traceback.format_exc()}")
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self.gauge.switch_to_next_goal() # save current goal metrics
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self.gauge.save_results()
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return logger.log_dir, e
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finally:
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self.sim.close_viewer()
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self.sim.close_video_writer()
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logger.info("✅ Pipeline execution finished.")
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logger.info(f"📁 Logging saved at: {logger.log_dir}")
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return logger.log_dir, None
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def reset_sim(self, sim_data: SimData):
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self.sim.reset()
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self.last_reset_time = sim_data.sim_time
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self.first_reset = True
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sim_data = self.sim.step()
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return sim_data
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def add_noise(self, sim_data: SimData):
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sim_data = deepcopy(sim_data)
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noise_cfg = self.sim_cfg.noise
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if not noise_cfg.enabled:
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return sim_data
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proprio = sim_data.proprio
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def add_uniform_noise(data, noise_level):
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for i in range(len(data)):
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noise = random.uniform(-noise_level, noise_level)
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data[i] += noise
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add_uniform_noise(proprio.joint.pos, noise_cfg.joint_pos)
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add_uniform_noise(proprio.joint.vel, noise_cfg.joint_vel)
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add_uniform_noise(proprio.base.lin_vel, noise_cfg.lin_vel)
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add_uniform_noise(proprio.base.ang_vel, noise_cfg.ang_vel)
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add_uniform_noise(proprio.imu.lin_vel, noise_cfg.lin_vel)
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add_uniform_noise(proprio.imu.ang_vel, noise_cfg.ang_vel)
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return sim_data
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