diff --git a/lerobot/common/envs/abstract.py b/lerobot/common/envs/abstract.py new file mode 100644 index 00000000..e69de29b diff --git a/lerobot/common/envs/aloha/assets/bimanual_viperx_ee_insertion.xml b/lerobot/common/envs/aloha/assets/bimanual_viperx_ee_insertion.xml new file mode 100644 index 00000000..8002838c --- /dev/null +++ b/lerobot/common/envs/aloha/assets/bimanual_viperx_ee_insertion.xml @@ -0,0 +1,59 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/assets/bimanual_viperx_ee_transfer_cube.xml b/lerobot/common/envs/aloha/assets/bimanual_viperx_ee_transfer_cube.xml new file mode 100644 index 00000000..05249ad2 --- /dev/null +++ b/lerobot/common/envs/aloha/assets/bimanual_viperx_ee_transfer_cube.xml @@ -0,0 +1,48 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/assets/bimanual_viperx_insertion.xml b/lerobot/common/envs/aloha/assets/bimanual_viperx_insertion.xml new file mode 100644 index 00000000..511f7947 --- /dev/null +++ b/lerobot/common/envs/aloha/assets/bimanual_viperx_insertion.xml @@ -0,0 +1,53 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/assets/bimanual_viperx_transfer_cube.xml b/lerobot/common/envs/aloha/assets/bimanual_viperx_transfer_cube.xml new file mode 100644 index 00000000..2d85a47c --- /dev/null +++ b/lerobot/common/envs/aloha/assets/bimanual_viperx_transfer_cube.xml @@ -0,0 +1,42 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/assets/scene.xml b/lerobot/common/envs/aloha/assets/scene.xml new file mode 100644 index 00000000..0f61b8a5 --- /dev/null +++ b/lerobot/common/envs/aloha/assets/scene.xml @@ -0,0 +1,38 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/assets/tabletop.stl b/lerobot/common/envs/aloha/assets/tabletop.stl new file mode 100644 index 00000000..ab35cdf7 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/tabletop.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_10_custom_finger_left.stl b/lerobot/common/envs/aloha/assets/vx300s_10_custom_finger_left.stl new file mode 100644 index 00000000..534c7af9 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_10_custom_finger_left.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_10_custom_finger_right.stl b/lerobot/common/envs/aloha/assets/vx300s_10_custom_finger_right.stl new file mode 100644 index 00000000..d6a492c2 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_10_custom_finger_right.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_10_gripper_finger.stl b/lerobot/common/envs/aloha/assets/vx300s_10_gripper_finger.stl new file mode 100644 index 00000000..d6df86be Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_10_gripper_finger.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_11_ar_tag.stl b/lerobot/common/envs/aloha/assets/vx300s_11_ar_tag.stl new file mode 100644 index 00000000..193014b6 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_11_ar_tag.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_1_base.stl b/lerobot/common/envs/aloha/assets/vx300s_1_base.stl new file mode 100644 index 00000000..5a7efda2 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_1_base.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_2_shoulder.stl b/lerobot/common/envs/aloha/assets/vx300s_2_shoulder.stl new file mode 100644 index 00000000..dc22aa7e Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_2_shoulder.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_3_upper_arm.stl b/lerobot/common/envs/aloha/assets/vx300s_3_upper_arm.stl new file mode 100644 index 00000000..111c586e Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_3_upper_arm.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_4_upper_forearm.stl b/lerobot/common/envs/aloha/assets/vx300s_4_upper_forearm.stl new file mode 100644 index 00000000..8170d21c Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_4_upper_forearm.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_5_lower_forearm.stl b/lerobot/common/envs/aloha/assets/vx300s_5_lower_forearm.stl new file mode 100644 index 00000000..39581f83 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_5_lower_forearm.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_6_wrist.stl b/lerobot/common/envs/aloha/assets/vx300s_6_wrist.stl new file mode 100644 index 00000000..ab8423e9 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_6_wrist.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_7_gripper.stl b/lerobot/common/envs/aloha/assets/vx300s_7_gripper.stl new file mode 100644 index 00000000..043db9ca Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_7_gripper.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_8_gripper_prop.stl b/lerobot/common/envs/aloha/assets/vx300s_8_gripper_prop.stl new file mode 100644 index 00000000..36099b42 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_8_gripper_prop.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_9_gripper_bar.stl b/lerobot/common/envs/aloha/assets/vx300s_9_gripper_bar.stl new file mode 100644 index 00000000..eba3caa2 Binary files /dev/null and b/lerobot/common/envs/aloha/assets/vx300s_9_gripper_bar.stl differ diff --git a/lerobot/common/envs/aloha/assets/vx300s_dependencies.xml b/lerobot/common/envs/aloha/assets/vx300s_dependencies.xml new file mode 100644 index 00000000..93037ab7 --- /dev/null +++ b/lerobot/common/envs/aloha/assets/vx300s_dependencies.xml @@ -0,0 +1,17 @@ + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/assets/vx300s_left.xml b/lerobot/common/envs/aloha/assets/vx300s_left.xml new file mode 100644 index 00000000..3af6c235 --- /dev/null +++ b/lerobot/common/envs/aloha/assets/vx300s_left.xml @@ -0,0 +1,59 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/assets/vx300s_right.xml b/lerobot/common/envs/aloha/assets/vx300s_right.xml new file mode 100644 index 00000000..495df478 --- /dev/null +++ b/lerobot/common/envs/aloha/assets/vx300s_right.xml @@ -0,0 +1,59 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lerobot/common/envs/aloha/constants.py b/lerobot/common/envs/aloha/constants.py new file mode 100644 index 00000000..927fb6d3 --- /dev/null +++ b/lerobot/common/envs/aloha/constants.py @@ -0,0 +1,97 @@ +from pathlib import Path + +### Simulation envs fixed constants +DT = 0.02 +JOINT_NAMES = ["waist", "shoulder", "elbow", "forearm_roll", "wrist_angle", "wrist_rotate"] +START_ARM_POSE = [ + 0, + -0.96, + 1.16, + 0, + -0.3, + 0, + 0.02239, + -0.02239, + 0, + -0.96, + 1.16, + 0, + -0.3, + 0, + 0.02239, + -0.02239, +] + +ASSETS_DIR = Path(__file__).parent.resolve() / "assets" # note: absolute path + +# Left finger position limits (qpos[7]), right_finger = -1 * left_finger +MASTER_GRIPPER_POSITION_OPEN = 0.02417 +MASTER_GRIPPER_POSITION_CLOSE = 0.01244 +PUPPET_GRIPPER_POSITION_OPEN = 0.05800 +PUPPET_GRIPPER_POSITION_CLOSE = 0.01844 + +# Gripper joint limits (qpos[6]) +MASTER_GRIPPER_JOINT_OPEN = 0.3083 +MASTER_GRIPPER_JOINT_CLOSE = -0.6842 +PUPPET_GRIPPER_JOINT_OPEN = 1.4910 +PUPPET_GRIPPER_JOINT_CLOSE = -0.6213 + +############################ Helper functions ############################ + +MASTER_GRIPPER_POSITION_NORMALIZE_FN = lambda x: (x - MASTER_GRIPPER_POSITION_CLOSE) / ( + MASTER_GRIPPER_POSITION_OPEN - MASTER_GRIPPER_POSITION_CLOSE +) +PUPPET_GRIPPER_POSITION_NORMALIZE_FN = lambda x: (x - PUPPET_GRIPPER_POSITION_CLOSE) / ( + PUPPET_GRIPPER_POSITION_OPEN - PUPPET_GRIPPER_POSITION_CLOSE +) +MASTER_GRIPPER_POSITION_UNNORMALIZE_FN = ( + lambda x: x * (MASTER_GRIPPER_POSITION_OPEN - MASTER_GRIPPER_POSITION_CLOSE) + + MASTER_GRIPPER_POSITION_CLOSE +) +PUPPET_GRIPPER_POSITION_UNNORMALIZE_FN = ( + lambda x: x * (PUPPET_GRIPPER_POSITION_OPEN - PUPPET_GRIPPER_POSITION_CLOSE) + + PUPPET_GRIPPER_POSITION_CLOSE +) +MASTER2PUPPET_POSITION_FN = lambda x: PUPPET_GRIPPER_POSITION_UNNORMALIZE_FN( + MASTER_GRIPPER_POSITION_NORMALIZE_FN(x) +) + +MASTER_GRIPPER_JOINT_NORMALIZE_FN = lambda x: (x - MASTER_GRIPPER_JOINT_CLOSE) / ( + MASTER_GRIPPER_JOINT_OPEN - MASTER_GRIPPER_JOINT_CLOSE +) +PUPPET_GRIPPER_JOINT_NORMALIZE_FN = lambda x: (x - PUPPET_GRIPPER_JOINT_CLOSE) / ( + PUPPET_GRIPPER_JOINT_OPEN - PUPPET_GRIPPER_JOINT_CLOSE +) +MASTER_GRIPPER_JOINT_UNNORMALIZE_FN = ( + lambda x: x * (MASTER_GRIPPER_JOINT_OPEN - MASTER_GRIPPER_JOINT_CLOSE) + MASTER_GRIPPER_JOINT_CLOSE +) +PUPPET_GRIPPER_JOINT_UNNORMALIZE_FN = ( + lambda x: x * (PUPPET_GRIPPER_JOINT_OPEN - PUPPET_GRIPPER_JOINT_CLOSE) + PUPPET_GRIPPER_JOINT_CLOSE +) +MASTER2PUPPET_JOINT_FN = lambda x: PUPPET_GRIPPER_JOINT_UNNORMALIZE_FN(MASTER_GRIPPER_JOINT_NORMALIZE_FN(x)) + +MASTER_GRIPPER_VELOCITY_NORMALIZE_FN = lambda x: x / ( + MASTER_GRIPPER_POSITION_OPEN - MASTER_GRIPPER_POSITION_CLOSE +) +PUPPET_GRIPPER_VELOCITY_NORMALIZE_FN = lambda x: x / ( + PUPPET_GRIPPER_POSITION_OPEN - PUPPET_GRIPPER_POSITION_CLOSE +) + +MASTER_POS2JOINT = ( + lambda x: MASTER_GRIPPER_POSITION_NORMALIZE_FN(x) + * (MASTER_GRIPPER_JOINT_OPEN - MASTER_GRIPPER_JOINT_CLOSE) + + MASTER_GRIPPER_JOINT_CLOSE +) +MASTER_JOINT2POS = lambda x: MASTER_GRIPPER_POSITION_UNNORMALIZE_FN( + (x - MASTER_GRIPPER_JOINT_CLOSE) / (MASTER_GRIPPER_JOINT_OPEN - MASTER_GRIPPER_JOINT_CLOSE) +) +PUPPET_POS2JOINT = ( + lambda x: PUPPET_GRIPPER_POSITION_NORMALIZE_FN(x) + * (PUPPET_GRIPPER_JOINT_OPEN - PUPPET_GRIPPER_JOINT_CLOSE) + + PUPPET_GRIPPER_JOINT_CLOSE +) +PUPPET_JOINT2POS = lambda x: PUPPET_GRIPPER_POSITION_UNNORMALIZE_FN( + (x - PUPPET_GRIPPER_JOINT_CLOSE) / (PUPPET_GRIPPER_JOINT_OPEN - PUPPET_GRIPPER_JOINT_CLOSE) +) + +MASTER_GRIPPER_JOINT_MID = (MASTER_GRIPPER_JOINT_OPEN + MASTER_GRIPPER_JOINT_CLOSE) / 2 diff --git a/lerobot/common/envs/aloha/env.py b/lerobot/common/envs/aloha/env.py new file mode 100644 index 00000000..70edf389 --- /dev/null +++ b/lerobot/common/envs/aloha/env.py @@ -0,0 +1,535 @@ +import collections +import importlib +from collections import deque +from typing import Optional + +import numpy as np +import torch +from dm_control import mujoco +from dm_control.rl import control +from dm_control.suite import base +from tensordict import TensorDict +from torchrl.data.tensor_specs import ( + BoundedTensorSpec, + CompositeSpec, + DiscreteTensorSpec, + UnboundedContinuousTensorSpec, +) +from torchrl.envs import EnvBase +from torchrl.envs.libs.gym import _gym_to_torchrl_spec_transform + +from lerobot.common.utils import set_seed + +from .constants import ( + ASSETS_DIR, + DT, + PUPPET_GRIPPER_POSITION_CLOSE, + PUPPET_GRIPPER_POSITION_NORMALIZE_FN, + PUPPET_GRIPPER_POSITION_UNNORMALIZE_FN, + PUPPET_GRIPPER_VELOCITY_NORMALIZE_FN, + START_ARM_POSE, +) +from .utils import sample_box_pose, sample_insertion_pose + +_has_gym = importlib.util.find_spec("gym") is not None + + +def make_ee_sim_env(task_name): + """ + Environment for simulated robot bi-manual manipulation, with end-effector control. + Action space: [left_arm_pose (7), # position and quaternion for end effector + left_gripper_positions (1), # normalized gripper position (0: close, 1: open) + right_arm_pose (7), # position and quaternion for end effector + right_gripper_positions (1),] # normalized gripper position (0: close, 1: open) + + Observation space: {"qpos": Concat[ left_arm_qpos (6), # absolute joint position + left_gripper_position (1), # normalized gripper position (0: close, 1: open) + right_arm_qpos (6), # absolute joint position + right_gripper_qpos (1)] # normalized gripper position (0: close, 1: open) + "qvel": Concat[ left_arm_qvel (6), # absolute joint velocity (rad) + left_gripper_velocity (1), # normalized gripper velocity (pos: opening, neg: closing) + right_arm_qvel (6), # absolute joint velocity (rad) + right_gripper_qvel (1)] # normalized gripper velocity (pos: opening, neg: closing) + "images": {"main": (480x640x3)} # h, w, c, dtype='uint8' + """ + if "sim_transfer_cube" in task_name: + xml_path = ASSETS_DIR / "bimanual_viperx_ee_transfer_cube.xml" + physics = mujoco.Physics.from_xml_path(xml_path) + task = TransferCubeEETask(random=False) + env = control.Environment( + physics, task, time_limit=20, control_timestep=DT, n_sub_steps=None, flat_observation=False + ) + elif "sim_insertion" in task_name: + xml_path = ASSETS_DIR / "bimanual_viperx_ee_insertion.xml" + physics = mujoco.Physics.from_xml_path(xml_path) + task = InsertionEETask(random=False) + env = control.Environment( + physics, task, time_limit=20, control_timestep=DT, n_sub_steps=None, flat_observation=False + ) + else: + raise NotImplementedError + return env + + +class BimanualViperXEETask(base.Task): + def __init__(self, random=None): + super().__init__(random=random) + + def before_step(self, action, physics): + a_len = len(action) // 2 + action_left = action[:a_len] + action_right = action[a_len:] + + # set mocap position and quat + # left + np.copyto(physics.data.mocap_pos[0], action_left[:3]) + np.copyto(physics.data.mocap_quat[0], action_left[3:7]) + # right + np.copyto(physics.data.mocap_pos[1], action_right[:3]) + np.copyto(physics.data.mocap_quat[1], action_right[3:7]) + + # set gripper + g_left_ctrl = PUPPET_GRIPPER_POSITION_UNNORMALIZE_FN(action_left[7]) + g_right_ctrl = PUPPET_GRIPPER_POSITION_UNNORMALIZE_FN(action_right[7]) + np.copyto(physics.data.ctrl, np.array([g_left_ctrl, -g_left_ctrl, g_right_ctrl, -g_right_ctrl])) + + def initialize_robots(self, physics): + # reset joint position + physics.named.data.qpos[:16] = START_ARM_POSE + + # reset mocap to align with end effector + # to obtain these numbers: + # (1) make an ee_sim env and reset to the same start_pose + # (2) get env._physics.named.data.xpos['vx300s_left/gripper_link'] + # get env._physics.named.data.xquat['vx300s_left/gripper_link'] + # repeat the same for right side + np.copyto(physics.data.mocap_pos[0], [-0.31718881, 0.5, 0.29525084]) + np.copyto(physics.data.mocap_quat[0], [1, 0, 0, 0]) + # right + np.copyto(physics.data.mocap_pos[1], np.array([0.31718881, 0.49999888, 0.29525084])) + np.copyto(physics.data.mocap_quat[1], [1, 0, 0, 0]) + + # reset gripper control + close_gripper_control = np.array( + [ + PUPPET_GRIPPER_POSITION_CLOSE, + -PUPPET_GRIPPER_POSITION_CLOSE, + PUPPET_GRIPPER_POSITION_CLOSE, + -PUPPET_GRIPPER_POSITION_CLOSE, + ] + ) + np.copyto(physics.data.ctrl, close_gripper_control) + + def initialize_episode(self, physics): + """Sets the state of the environment at the start of each episode.""" + super().initialize_episode(physics) + + @staticmethod + def get_qpos(physics): + qpos_raw = physics.data.qpos.copy() + left_qpos_raw = qpos_raw[:8] + right_qpos_raw = qpos_raw[8:16] + left_arm_qpos = left_qpos_raw[:6] + right_arm_qpos = right_qpos_raw[:6] + left_gripper_qpos = [PUPPET_GRIPPER_POSITION_NORMALIZE_FN(left_qpos_raw[6])] + right_gripper_qpos = [PUPPET_GRIPPER_POSITION_NORMALIZE_FN(right_qpos_raw[6])] + return np.concatenate([left_arm_qpos, left_gripper_qpos, right_arm_qpos, right_gripper_qpos]) + + @staticmethod + def get_qvel(physics): + qvel_raw = physics.data.qvel.copy() + left_qvel_raw = qvel_raw[:8] + right_qvel_raw = qvel_raw[8:16] + left_arm_qvel = left_qvel_raw[:6] + right_arm_qvel = right_qvel_raw[:6] + left_gripper_qvel = [PUPPET_GRIPPER_VELOCITY_NORMALIZE_FN(left_qvel_raw[6])] + right_gripper_qvel = [PUPPET_GRIPPER_VELOCITY_NORMALIZE_FN(right_qvel_raw[6])] + return np.concatenate([left_arm_qvel, left_gripper_qvel, right_arm_qvel, right_gripper_qvel]) + + @staticmethod + def get_env_state(physics): + raise NotImplementedError + + def get_observation(self, physics): + # note: it is important to do .copy() + obs = collections.OrderedDict() + obs["qpos"] = self.get_qpos(physics) + obs["qvel"] = self.get_qvel(physics) + obs["env_state"] = self.get_env_state(physics) + obs["images"] = dict() + obs["images"]["top"] = physics.render(height=480, width=640, camera_id="top") + obs["images"]["angle"] = physics.render(height=480, width=640, camera_id="angle") + obs["images"]["vis"] = physics.render(height=480, width=640, camera_id="front_close") + # used in scripted policy to obtain starting pose + obs["mocap_pose_left"] = np.concatenate( + [physics.data.mocap_pos[0], physics.data.mocap_quat[0]] + ).copy() + obs["mocap_pose_right"] = np.concatenate( + [physics.data.mocap_pos[1], physics.data.mocap_quat[1]] + ).copy() + + # used when replaying joint trajectory + obs["gripper_ctrl"] = physics.data.ctrl.copy() + return obs + + def get_reward(self, physics): + raise NotImplementedError + + +class TransferCubeEETask(BimanualViperXEETask): + def __init__(self, random=None): + super().__init__(random=random) + self.max_reward = 4 + + def initialize_episode(self, physics): + """Sets the state of the environment at the start of each episode.""" + self.initialize_robots(physics) + # randomize box position + cube_pose = sample_box_pose() + box_start_idx = physics.model.name2id("red_box_joint", "joint") + np.copyto(physics.data.qpos[box_start_idx : box_start_idx + 7], cube_pose) + # print(f"randomized cube position to {cube_position}") + + super().initialize_episode(physics) + + @staticmethod + def get_env_state(physics): + env_state = physics.data.qpos.copy()[16:] + return env_state + + def get_reward(self, physics): + # return whether left gripper is holding the box + all_contact_pairs = [] + for i_contact in range(physics.data.ncon): + id_geom_1 = physics.data.contact[i_contact].geom1 + id_geom_2 = physics.data.contact[i_contact].geom2 + name_geom_1 = physics.model.id2name(id_geom_1, "geom") + name_geom_2 = physics.model.id2name(id_geom_2, "geom") + contact_pair = (name_geom_1, name_geom_2) + all_contact_pairs.append(contact_pair) + + touch_left_gripper = ("red_box", "vx300s_left/10_left_gripper_finger") in all_contact_pairs + touch_right_gripper = ("red_box", "vx300s_right/10_right_gripper_finger") in all_contact_pairs + touch_table = ("red_box", "table") in all_contact_pairs + + reward = 0 + if touch_right_gripper: + reward = 1 + if touch_right_gripper and not touch_table: # lifted + reward = 2 + if touch_left_gripper: # attempted transfer + reward = 3 + if touch_left_gripper and not touch_table: # successful transfer + reward = 4 + return reward + + +class InsertionEETask(BimanualViperXEETask): + def __init__(self, random=None): + super().__init__(random=random) + self.max_reward = 4 + + def initialize_episode(self, physics): + """Sets the state of the environment at the start of each episode.""" + self.initialize_robots(physics) + # randomize peg and socket position + peg_pose, socket_pose = sample_insertion_pose() + id2index = lambda j_id: 16 + (j_id - 16) * 7 # first 16 is robot qpos, 7 is pose dim # hacky + + peg_start_id = physics.model.name2id("red_peg_joint", "joint") + peg_start_idx = id2index(peg_start_id) + np.copyto(physics.data.qpos[peg_start_idx : peg_start_idx + 7], peg_pose) + # print(f"randomized cube position to {cube_position}") + + socket_start_id = physics.model.name2id("blue_socket_joint", "joint") + socket_start_idx = id2index(socket_start_id) + np.copyto(physics.data.qpos[socket_start_idx : socket_start_idx + 7], socket_pose) + # print(f"randomized cube position to {cube_position}") + + super().initialize_episode(physics) + + @staticmethod + def get_env_state(physics): + env_state = physics.data.qpos.copy()[16:] + return env_state + + def get_reward(self, physics): + # return whether peg touches the pin + all_contact_pairs = [] + for i_contact in range(physics.data.ncon): + id_geom_1 = physics.data.contact[i_contact].geom1 + id_geom_2 = physics.data.contact[i_contact].geom2 + name_geom_1 = physics.model.id2name(id_geom_1, "geom") + name_geom_2 = physics.model.id2name(id_geom_2, "geom") + contact_pair = (name_geom_1, name_geom_2) + all_contact_pairs.append(contact_pair) + + touch_right_gripper = ("red_peg", "vx300s_right/10_right_gripper_finger") in all_contact_pairs + touch_left_gripper = ( + ("socket-1", "vx300s_left/10_left_gripper_finger") in all_contact_pairs + or ("socket-2", "vx300s_left/10_left_gripper_finger") in all_contact_pairs + or ("socket-3", "vx300s_left/10_left_gripper_finger") in all_contact_pairs + or ("socket-4", "vx300s_left/10_left_gripper_finger") in all_contact_pairs + ) + + peg_touch_table = ("red_peg", "table") in all_contact_pairs + socket_touch_table = ( + ("socket-1", "table") in all_contact_pairs + or ("socket-2", "table") in all_contact_pairs + or ("socket-3", "table") in all_contact_pairs + or ("socket-4", "table") in all_contact_pairs + ) + peg_touch_socket = ( + ("red_peg", "socket-1") in all_contact_pairs + or ("red_peg", "socket-2") in all_contact_pairs + or ("red_peg", "socket-3") in all_contact_pairs + or ("red_peg", "socket-4") in all_contact_pairs + ) + pin_touched = ("red_peg", "pin") in all_contact_pairs + + reward = 0 + if touch_left_gripper and touch_right_gripper: # touch both + reward = 1 + if ( + touch_left_gripper and touch_right_gripper and (not peg_touch_table) and (not socket_touch_table) + ): # grasp both + reward = 2 + if peg_touch_socket and (not peg_touch_table) and (not socket_touch_table): # peg and socket touching + reward = 3 + if pin_touched: # successful insertion + reward = 4 + return reward + + +class AlohaEnv(EnvBase): + def __init__( + self, + task, + frame_skip: int = 1, + from_pixels: bool = False, + pixels_only: bool = False, + image_size=None, + seed=1337, + device="cpu", + num_prev_obs=1, + num_prev_action=0, + ): + super().__init__(device=device, batch_size=[]) + self.frame_skip = frame_skip + self.from_pixels = from_pixels + self.pixels_only = pixels_only + self.image_size = image_size + self.num_prev_obs = num_prev_obs + self.num_prev_action = num_prev_action + + if pixels_only: + assert from_pixels + if from_pixels: + assert image_size + + if not _has_gym: + raise ImportError("Cannot import gym.") + + if not from_pixels: + raise NotImplementedError() + + if "sim_transfer_cube" in task: + xml_path = ASSETS_DIR / "bimanual_viperx_ee_transfer_cube.xml" + physics = mujoco.Physics.from_xml_path(xml_path) + task = TransferCubeEETask(random=False) + env = control.Environment( + physics, task, time_limit=20, control_timestep=DT, n_sub_steps=None, flat_observation=False + ) + elif "sim_insertion" in task: + xml_path = ASSETS_DIR / "bimanual_viperx_ee_insertion.xml" + physics = mujoco.Physics.from_xml_path(xml_path) + task = InsertionEETask(random=False) + env = control.Environment( + physics, task, time_limit=20, control_timestep=DT, n_sub_steps=None, flat_observation=False + ) + else: + raise NotImplementedError + + self._env = env + + self._make_spec() + self._current_seed = self.set_seed(seed) + + if self.num_prev_obs > 0: + self._prev_obs_image_queue = deque(maxlen=self.num_prev_obs) + self._prev_obs_state_queue = deque(maxlen=self.num_prev_obs) + if self.num_prev_action > 0: + raise NotImplementedError() + # self._prev_action_queue = deque(maxlen=self.num_prev_action) + + def render(self, mode="rgb_array", width=384, height=384): + if width != height: + raise NotImplementedError() + tmp = self._env.render_size + self._env.render_size = width + out = self._env.render(mode) + self._env.render_size = tmp + return out + + def _format_raw_obs(self, raw_obs): + if self.from_pixels: + image = torch.from_numpy(raw_obs["image"]) + obs = {"image": image} + + if not self.pixels_only: + obs["state"] = torch.from_numpy(raw_obs["agent_pos"]).type(torch.float32) + else: + # TODO: + obs = {"state": torch.from_numpy(raw_obs["observation"]).type(torch.float32)} + + return obs + + def _reset(self, tensordict: Optional[TensorDict] = None): + td = tensordict + if td is None or td.is_empty(): + # we need to handle seed iteration, since self._env.reset() rely an internal _seed. + self._current_seed += 1 + self.set_seed(self._current_seed) + raw_obs = self._env.reset() + assert self._current_seed == self._env._seed + + obs = self._format_raw_obs(raw_obs) + + if self.num_prev_obs > 0: + stacked_obs = {} + if "image" in obs: + self._prev_obs_image_queue = deque( + [obs["image"]] * (self.num_prev_obs + 1), maxlen=(self.num_prev_obs + 1) + ) + stacked_obs["image"] = torch.stack(list(self._prev_obs_image_queue)) + if "state" in obs: + self._prev_obs_state_queue = deque( + [obs["state"]] * (self.num_prev_obs + 1), maxlen=(self.num_prev_obs + 1) + ) + stacked_obs["state"] = torch.stack(list(self._prev_obs_state_queue)) + obs = stacked_obs + + td = TensorDict( + { + "observation": TensorDict(obs, batch_size=[]), + "done": torch.tensor([False], dtype=torch.bool), + }, + batch_size=[], + ) + else: + raise NotImplementedError() + return td + + def _step(self, tensordict: TensorDict): + td = tensordict + action = td["action"].numpy() + # step expects shape=(4,) so we pad if necessary + # TODO(rcadene): add info["is_success"] and info["success"] ? + sum_reward = 0 + + if action.ndim == 1: + action = einops.repeat(action, "c -> t c", t=self.frame_skip) + else: + if self.frame_skip > 1: + raise NotImplementedError() + + num_action_steps = action.shape[0] + for i in range(num_action_steps): + raw_obs, reward, done, info = self._env.step(action[i]) + sum_reward += reward + + obs = self._format_raw_obs(raw_obs) + + if self.num_prev_obs > 0: + stacked_obs = {} + if "image" in obs: + self._prev_obs_image_queue.append(obs["image"]) + stacked_obs["image"] = torch.stack(list(self._prev_obs_image_queue)) + if "state" in obs: + self._prev_obs_state_queue.append(obs["state"]) + stacked_obs["state"] = torch.stack(list(self._prev_obs_state_queue)) + obs = stacked_obs + + td = TensorDict( + { + "observation": TensorDict(obs, batch_size=[]), + "reward": torch.tensor([sum_reward], dtype=torch.float32), + # succes and done are true when coverage > self.success_threshold in env + "done": torch.tensor([done], dtype=torch.bool), + "success": torch.tensor([done], dtype=torch.bool), + }, + batch_size=[], + ) + return td + + def _make_spec(self): + obs = {} + if self.from_pixels: + image_shape = (3, self.image_size, self.image_size) + if self.num_prev_obs > 0: + image_shape = (self.num_prev_obs + 1, *image_shape) + + obs["image"] = BoundedTensorSpec( + low=0, + high=1, + shape=image_shape, + dtype=torch.float32, + device=self.device, + ) + if not self.pixels_only: + state_shape = self._env.observation_space["agent_pos"].shape + if self.num_prev_obs > 0: + state_shape = (self.num_prev_obs + 1, *state_shape) + + obs["state"] = BoundedTensorSpec( + low=0, + high=512, + shape=state_shape, + dtype=torch.float32, + device=self.device, + ) + else: + # TODO(rcadene): add observation_space achieved_goal and desired_goal? + state_shape = self._env.observation_space["observation"].shape + if self.num_prev_obs > 0: + state_shape = (self.num_prev_obs + 1, *state_shape) + + obs["state"] = UnboundedContinuousTensorSpec( + # TODO: + shape=state_shape, + dtype=torch.float32, + device=self.device, + ) + self.observation_spec = CompositeSpec({"observation": obs}) + + self.action_spec = _gym_to_torchrl_spec_transform( + self._env.action_space, + device=self.device, + ) + + self.reward_spec = UnboundedContinuousTensorSpec( + shape=(1,), + dtype=torch.float32, + device=self.device, + ) + + self.done_spec = CompositeSpec( + { + "done": DiscreteTensorSpec( + 2, + shape=(1,), + dtype=torch.bool, + device=self.device, + ), + "success": DiscreteTensorSpec( + 2, + shape=(1,), + dtype=torch.bool, + device=self.device, + ), + } + ) + + def _set_seed(self, seed: Optional[int]): + set_seed(seed) + self._env.seed(seed) diff --git a/lerobot/common/envs/aloha/utils.py b/lerobot/common/envs/aloha/utils.py new file mode 100644 index 00000000..5ac8b955 --- /dev/null +++ b/lerobot/common/envs/aloha/utils.py @@ -0,0 +1,39 @@ +import numpy as np + + +def sample_box_pose(): + x_range = [0.0, 0.2] + y_range = [0.4, 0.6] + z_range = [0.05, 0.05] + + ranges = np.vstack([x_range, y_range, z_range]) + cube_position = np.random.uniform(ranges[:, 0], ranges[:, 1]) + + cube_quat = np.array([1, 0, 0, 0]) + return np.concatenate([cube_position, cube_quat]) + + +def sample_insertion_pose(): + # Peg + x_range = [0.1, 0.2] + y_range = [0.4, 0.6] + z_range = [0.05, 0.05] + + ranges = np.vstack([x_range, y_range, z_range]) + peg_position = np.random.uniform(ranges[:, 0], ranges[:, 1]) + + peg_quat = np.array([1, 0, 0, 0]) + peg_pose = np.concatenate([peg_position, peg_quat]) + + # Socket + x_range = [-0.2, -0.1] + y_range = [0.4, 0.6] + z_range = [0.05, 0.05] + + ranges = np.vstack([x_range, y_range, z_range]) + socket_position = np.random.uniform(ranges[:, 0], ranges[:, 1]) + + socket_quat = np.array([1, 0, 0, 0]) + socket_pose = np.concatenate([socket_position, socket_quat]) + + return peg_pose, socket_pose diff --git a/lerobot/common/envs/factory.py b/lerobot/common/envs/factory.py index 984b866a..ecb3e835 100644 --- a/lerobot/common/envs/factory.py +++ b/lerobot/common/envs/factory.py @@ -23,6 +23,10 @@ def make_env(cfg, transform=None): # assert kwargs["seed"] > 200, "Seed 0-200 are used for the demonstration dataset, so we don't want to seed the eval env with this range." clsfunc = PushtEnv + elif cfg.env.name == "aloha": + from lerobot.common.envs.aloha.env import AlohaEnv + + clsfunc = AlohaEnv else: raise ValueError(cfg.env.name) diff --git a/poetry.lock b/poetry.lock index 9a35071b..761d9bd5 100644 --- a/poetry.lock +++ b/poetry.lock @@ -503,6 +503,37 @@ files = [ {file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"}, ] +[[package]] +name = "dm-control" +version = "1.0.14" +description = "Continuous control environments and MuJoCo Python bindings." +optional = false +python-versions = ">=3.8" +files = [ + {file = "dm_control-1.0.14-py3-none-any.whl", hash = "sha256:883c63244a7ebf598700a97564ed19fffd3479ca79efd090aed881609cdb9fc6"}, + {file = "dm_control-1.0.14.tar.gz", hash = "sha256:def1ece747b6f175c581150826b50f1a6134086dab34f8f3fd2d088ea035cf3d"}, +] + +[package.dependencies] +absl-py = ">=0.7.0" +dm-env = "*" +dm-tree = "!=0.1.2" +glfw = "*" +labmaze = "*" +lxml = "*" +mujoco = ">=2.3.7" +numpy = ">=1.9.0" +protobuf = ">=3.19.4" +pyopengl = 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