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v0.1.7; fix env_command_range prob

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wty-yy
2026-01-08 16:55:44 +08:00
parent 47755ce06c
commit 836a4e544f
2 changed files with 7 additions and 5 deletions
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4
UPDATE.md
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@@ -1,6 +1,8 @@
# 20260107 # 20260107
## v0.1.7 ## v0.1.7
Fix bug: 修复`cfg.commands.dynamic_resample_commands=False`时, 未根据环境调整指令采样范围的问题 Fix bug:
1. 修复`cfg.commands.dynamic_resample_commands=False`时, 未根据环境调整指令采样范围的问题
2. 修复`env_command_ranges`初始值问题
## v0.1.6 ## v0.1.6
1. 加入`go2_rem_cts`, student使用MoE结构, teacher使用普通CTS, 使用非共享权重和全goal输入 1. 加入`go2_rem_cts`, student使用MoE结构, teacher使用普通CTS, 使用非共享权重和全goal输入
2. 加入`move_down_by_accumulated_xy_command`选择是否通过累计速度来降低等级 2. 加入`move_down_by_accumulated_xy_command`选择是否通过累计速度来降低等级

8
legged_gym/envs/base/legged_robot.py
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@@ -830,10 +830,10 @@ class LeggedRobot(BaseTask):
self.last_robot_props_update_step = torch.zeros(self.num_envs, dtype=torch.long, device=self.device, requires_grad=False) self.last_robot_props_update_step = torch.zeros(self.num_envs, dtype=torch.long, device=self.device, requires_grad=False)
self.turn_over_timer = torch.zeros(self.num_envs, dtype=torch.float, device=self.device, requires_grad=False) self.turn_over_timer = torch.zeros(self.num_envs, dtype=torch.float, device=self.device, requires_grad=False)
self.env_command_ranges = { self.env_command_ranges = {
'lin_vel_x': torch.zeros((self.num_envs, 2), dtype=torch.float, device=self.device, requires_grad=False), 'lin_vel_x': torch.tensor(self.command_ranges['lin_vel_x'], device=self.device, requires_grad=False).repeat(self.num_envs, 1),
'lin_vel_y': torch.zeros((self.num_envs, 2), dtype=torch.float, device=self.device, requires_grad=False), 'lin_vel_y': torch.tensor(self.command_ranges['lin_vel_y'], device=self.device, requires_grad=False).repeat(self.num_envs, 1),
'ang_vel_yaw': torch.zeros((self.num_envs, 2), dtype=torch.float, device=self.device, requires_grad=False), 'ang_vel_yaw': torch.tensor(self.command_ranges['ang_vel_yaw'], device=self.device, requires_grad=False).repeat(self.num_envs, 1),
'heading': torch.zeros((self.num_envs, 2), dtype=torch.float, device=self.device, requires_grad=False), 'heading': torch.tensor(self.command_ranges['heading'], device=self.device, requires_grad=False).repeat(self.num_envs, 1),
} }
self._update_env_command_ranges() self._update_env_command_ranges()