cyy/go2_rl_gym
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

v1.0.2-rc1; mv rem_cts to moe_cts, moe_cts to moe_no_goal_cts, fix rem params same as moe, add --robogauge to start

Browse Source
This commit is contained in:
wty-yy
2026-01-26 17:48:34 +08:00
parent 2aed91e7ce
commit 1798e67c29
23 changed files with 438 additions and 409 deletions
Download Patch File Download Diff File Expand all files Collapse all files

40
legged_gym/envs/go2/go2_config_vanilla.py
View File

@@ -1,17 +1,17 @@
# -*- coding: utf-8 -*-
'''
@File : go2_config_vanilla.py
@Time : 2026/01/10 02:26:04
@Time : 2026/01/10 02:27:28
@Author : wty-yy
@Version : 1.0
@Blog : https://wty-yy.github.io/
@Desc : Go2 vanilla training config
episode length 25, resample commands 5 sec,
open move_down_by_accumulated_xy_command, dynamic_resample_commands
close heading_command, zero_command_curriculum, limit_vel_prob, command_range_curriculum, dynamic_sigma
@Desc : Go2 vanilla training config, same as unitree rl gym except domain randomization and rewards
episode length 20, resample commands 10 sec,
open heading_command
close move_down_by_accumulated_xy_command, dynamic_resample_commands, zero_command_curriculum, limit_vel_prob, command_range_curriculum, dynamic_sigma
'''
import math
from legged_gym.envs.base.legged_robot_config import LeggedRobotCfg, LeggedRobotCfgPPO, LeggedRobotCfgCTS, LeggedRobotCfgMoECTS, LeggedRobotCfgMoECTS, LeggedRobotCfgMCPCTS, LeggedRobotCfgACMoECTS, LeggedRobotCfgDualMoECTS, LeggedRobotCfgREMCTS
from legged_gym.envs.base.legged_robot_config import LeggedRobotCfg, LeggedRobotCfgPPO, LeggedRobotCfgCTS, LeggedRobotCfgMoENGCTS, LeggedRobotCfgMoENGCTS, LeggedRobotCfgMCPCTS, LeggedRobotCfgACMoECTS, LeggedRobotCfgDualMoECTS, LeggedRobotCfgMoECTS
class GO2Cfg(LeggedRobotCfg):
class init_state(LeggedRobotCfg.init_state):
@@ -48,7 +48,7 @@ class GO2Cfg(LeggedRobotCfg):
num_privileged_obs = 45 + 3 + 4 + 12 + 12 + 187 # 263
# num_privileged_obs = 45 + 3 + 187 # 235
# num_privileged_obs = 48 # without height measurements
episode_length_s = 25
episode_length_s = 20
class domain_rand(LeggedRobotCfg.domain_rand):
### Robot properties ###
@@ -105,14 +105,14 @@ class GO2Cfg(LeggedRobotCfg):
# terrain_proportions = [0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0]
# terrain_proportions = [0.3, 0.3, 0.3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1]
# terrain_proportions = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0]
move_down_by_accumulated_xy_command = True # move down the terrain curriculum based on accumulated xy command distance instead of absolute distance
move_down_by_accumulated_xy_command = False # move down the terrain curriculum based on accumulated xy command distance instead of absolute distance
class commands(LeggedRobotCfg.commands):
curriculum = False
max_curriculum = 1.
num_commands = 4 # default: lin_vel_x, lin_vel_y, ang_vel_yaw (in heading mode ang_vel_yaw is recomputed from heading error)
resampling_time = 5. # time before command are changed[s]
heading_command = False # if true: compute ang vel command from heading error
resampling_time = 10. # time before command are changed[s]
heading_command = True # if true: compute ang vel command from heading error
# start training with zero commands and then gradually increase zero command probability
zero_command_curriculum = None
# zero_command_curriculum = {'start_iter': 0, 'end_iter': 1500, 'start_value': 0.0, 'end_value': 0.1}
@@ -121,7 +121,7 @@ class GO2Cfg(LeggedRobotCfg):
limit_vel_invert_when_continuous = True # invert the limit logic when using continuous sample limit velocity commands
limit_vel = {"lin_vel_x": [-1, 1], "lin_vel_y": [-1, 1], "ang_vel_yaw": [-1, 0, 1]} # sample vel commands from min [-1] or zero [0] or max [1] range only
stop_heading_at_limit = True # stop heading updates when vel is limited
dynamic_resample_commands = True # sample commands with low bounds
dynamic_resample_commands = False # sample commands with low bounds
command_range_curriculum = []
# command_range_curriculum = [{ # list for command range curriculums at specific training iterations
# 'iter': 20000, # training iteration at which the command ranges are updated
@@ -243,17 +243,17 @@ class GO2CfgCTS(LeggedRobotCfgCTS):
latent_dim = 32
norm_type = 'l2norm'
class GO2CfgMoECTS(LeggedRobotCfgMoECTS):
class policy(LeggedRobotCfgMoECTS.policy):
class GO2CfgMoENGCTS(LeggedRobotCfgMoENGCTS):
class policy(LeggedRobotCfgMoENGCTS.policy):
obs_no_goal_mask = [True] * 6 + [False] * 3 + [True] * 36 # mask for obs without command info
student_expert_num = 8 # number of experts in the student model
class algorithm(LeggedRobotCfgMoECTS.algorithm):
class algorithm(LeggedRobotCfgMoENGCTS.algorithm):
load_balance_coef = 0.01
class runner(LeggedRobotCfgMoECTS.runner):
class runner(LeggedRobotCfgMoENGCTS.runner):
run_name = ''
experiment_name = 'go2_moe_cts'
experiment_name = 'go2_moe_no_goal_cts'
max_iterations = 150000
save_interval = 500
@@ -288,12 +288,12 @@ class GO2CfgDualMoECTS(LeggedRobotCfgDualMoECTS):
max_iterations = 150000
save_interval = 500
class GO2CfgREMCTS(LeggedRobotCfgREMCTS):
class policy(LeggedRobotCfgREMCTS.policy):
class GO2CfgMoECTS(LeggedRobotCfgMoECTS):
class policy(LeggedRobotCfgMoECTS.policy):
expert_num = 8 # number of experts in the student model
class runner(LeggedRobotCfgREMCTS.runner):
class runner(LeggedRobotCfgMoECTS.runner):
run_name = ''
experiment_name = 'go2_rem_cts'
experiment_name = 'go2_moe_cts'
max_iterations = 150000
save_interval = 500