whut/AutoCalib-Workshop
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

feat:完善仿真环境

Browse Source
This commit is contained in:
li-shihao-code
2026-05-04 10:48:06 +08:00
parent 1cc1ed1544
commit df884252ff
2 changed files with 15 additions and 336 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+15 -1
View File
@@ -8,6 +8,7 @@
3. [输出的 ROS 2 话题](#3-输出的-ros-2-话题)
4. [团队协作与 Git 配置指南 (必读)](#4-团队协作与-git-配置指南-必读)
5. [开发与分支规范](#5-开发与分支规范)
6. [相关文档](#6-相关文档)
---
@@ -213,4 +214,17 @@ git lfs track "*.usd"
# 3. 提交 .gitattributes 文件
git add .gitattributes
git commit -m "Add Git LFS tracking for large files"
⚠️ 注意：如果已经提交了大文件到历史记录，需要使用 git lfs migrate 来重写历史，否则只是追踪新文件。
⚠️ 注意：如果已经提交了大文件到历史记录，需要使用 git lfs migrate 来重写历史，否则只是追踪新文件。
---
## 6. 相关文档
本项目包含多个子模块，相关文档位置如下：
| 文档 | 路径 | 说明 |
|------|------|------|
| **AGV 标定系统总述** | [`agv_calib_brain/README.md`](./agv_calib_brain/README.md) | 自动化标定车间整体架构、核心能力、快速开始 |
| **仿真启动指南** | [`agv_calib_brain/SIMULATION_GUIDE.md`](./agv_calib_brain/SIMULATION_GUIDE.md) | 如何单独启动 Isaac 仿真各组件 |
| **源码目录说明** | [`agv_calib_brain/src/README.md`](./agv_calib_brain/src/README.md) | 源码组织结构、边界规则 |
| **Isaac 仿真车间** | 本文档 | Isaac Sim 环境配置、基础仿真运行 |
build_calibration_room.py
-335
View File
@@ -1,335 +0,0 @@
import os
os.environ["OMNI_KIT_ACCEPT_EULA"] = "YES"
from isaacsim import SimulationApp
simulation_app = SimulationApp({"headless": False})
from omni.isaac.core.utils.extensions import enable_extension
enable_extension("omni.isaac.ros2_bridge")
simulation_app.update()
import numpy as np
from PIL import Image
import omni.kit.commands
from pathlib import Path
# 【底层基石 USD API】
import omni.usd
from pxr import Gf, Sdf, UsdShade, UsdGeom, Vt, PhysxSchema
from omni.isaac.core import World
from omni.isaac.core.objects import FixedCuboid
# 【新增引入】DynamicCuboid 用于生成受物理世界重力影响的动态刚体车辆
from omni.isaac.core.objects import DynamicCuboid
from omni.isaac.core.utils.prims import create_prim
from omni.isaac.core.utils.viewports import set_camera_view
from omni.isaac.core.utils.rotations import euler_angles_to_quat
from omni.isaac.sensor import Camera
import omni.replicator.core as rep
import omni.graph.core as og
from omni.isaac.core.objects import VisualCuboid
# 【引入 URDF 导入器和机器人核心类】
import omni.kit.commands
from omni.importer.urdf import _urdf
from omni.isaac.core.robots import Robot
from omni.isaac.core.utils.stage import add_reference_to_stage
def create_checkerboard_image(filepath="checkerboard.png", rows=6, cols=9, square_size_px=500):
width = cols * square_size_px
height = rows * square_size_px
img = np.ones((height, width, 3), dtype=np.uint8) * 255
for r in range(rows):
for c in range(cols):
if (r + c) % 2 == 1:
img[r*square_size_px:(r+1)*square_size_px, c*square_size_px:(c+1)*square_size_px] = 0
border = square_size_px
img_with_border = np.pad(img, pad_width=((border, border), (border, border), (0, 0)), mode='constant', constant_values=255)
pil_img = Image.fromarray(img_with_border)
abs_filepath = Path(filepath).resolve()
pil_img.save(abs_filepath)
usd_filepath = str(abs_filepath).replace("\\", "/")
print(f"[*] 棋盘格纹理已自动生成: {usd_filepath}")
return usd_filepath
def add_corner_rotary_lidars(room_length=10.0, room_width=6.0, height=3.5,
lidar_config="Example_Rotary", topic_prefix="/workshop/lidar"):
offset = 0.3
x_pos = (room_length / 2.0) - offset
y_pos = (room_width / 2.0) - offset
lidar_configs = [
{"name": "FL", "pos": [ x_pos, y_pos, height], "yaw": np.degrees(np.arctan2(-y_pos, -x_pos))},
{"name": "FR", "pos": [ x_pos, -y_pos, height], "yaw": np.degrees(np.arctan2( y_pos, -x_pos))},
{"name": "BL", "pos": [-x_pos, y_pos, height], "yaw": np.degrees(np.arctan2(-y_pos, x_pos))},
{"name": "BR", "pos": [-x_pos, -y_pos, height], "yaw": np.degrees(np.arctan2( y_pos, x_pos))}
]
keys = og.Controller.Keys
graph_path = "/World/ROS2_Lidar_Graph"
nodes = [("OnTick", "omni.graph.action.OnTick"), ("ReadSimTime", "omni.isaac.core_nodes.IsaacReadSimulationTime"), ("PublishTF", "omni.isaac.ros2_bridge.ROS2PublishTransformTree")]
connections = [("OnTick.outputs:tick", "PublishTF.inputs:execIn"), ("ReadSimTime.outputs:simulationTime", "PublishTF.inputs:timeStamp")]
set_values = []
lidar_paths = []
for cfg in lidar_configs:
lidar_path = f"/World/Sensors/Lidar_{cfg['name']}"
lidar_paths.append(lidar_path)
quat = euler_angles_to_quat(np.array([0, 15.0, cfg['yaw']]), degrees=True)
orientation = Gf.Quatd(quat[0], quat[1], quat[2], quat[3])
omni.kit.commands.execute("IsaacSensorCreateRtxLidar", path=lidar_path, parent=None, config=lidar_config, translation=Gf.Vec3d(*cfg["pos"]), orientation=orientation)
render_product = rep.create.render_product(lidar_path, [1, 1])
helper_name = f"ROS2LidarHelper_{cfg['name']}"
nodes.append((helper_name, "omni.isaac.ros2_bridge.ROS2RtxLidarHelper"))
connections.append(("OnTick.outputs:tick", f"{helper_name}.inputs:execIn"))
set_values.extend([
(f"{helper_name}.inputs:renderProductPath", str(render_product.path)), (f"{helper_name}.inputs:topicName", f"{topic_prefix}/{cfg['name'].lower()}/pointcloud"),
(f"{helper_name}.inputs:frameId", f"Lidar_{cfg['name']}"), (f"{helper_name}.inputs:type", "point_cloud"), (f"{helper_name}.inputs:fullScan", True)
])
set_values.append(("PublishTF.inputs:targetPrims", lidar_paths))
og.Controller.edit({"graph_path": graph_path, "evaluator_name": "execution"}, {keys.CREATE_NODES: nodes, keys.CONNECT: connections, keys.SET_VALUES: set_values})
def create_raw_usd_material(stage, mat_path, tex_path):
material = UsdShade.Material.Define(stage, mat_path)
pbr_shader = UsdShade.Shader.Define(stage, f"{mat_path}/PBRShader")
pbr_shader.CreateIdAttr("UsdPreviewSurface")
pbr_shader.CreateInput("roughness", Sdf.ValueTypeNames.Float).Set(1.0)
pbr_shader.CreateInput("metallic", Sdf.ValueTypeNames.Float).Set(0.0)
tex_sampler = UsdShade.Shader.Define(stage, f"{mat_path}/diffuseTexture")
tex_sampler.CreateIdAttr("UsdUVTexture")
tex_sampler.CreateInput("file", Sdf.ValueTypeNames.Asset).Set(Sdf.AssetPath(tex_path))
tex_sampler.CreateInput("magFilter", Sdf.ValueTypeNames.Token).Set("nearest")
tex_sampler.CreateInput("minFilter", Sdf.ValueTypeNames.Token).Set("nearest")
st_reader = UsdShade.Shader.Define(stage, f"{mat_path}/stReader")
st_reader.CreateIdAttr("UsdPrimvarReader_float2")
st_reader.CreateInput("varname", Sdf.ValueTypeNames.Token).Set("st")
tex_sampler.CreateInput("st", Sdf.ValueTypeNames.Float2).ConnectToSource(st_reader.ConnectableAPI(), "result")
pbr_shader.CreateInput("diffuseColor", Sdf.ValueTypeNames.Color3f).ConnectToSource(tex_sampler.ConnectableAPI(), "rgb")
material.CreateSurfaceOutput().ConnectToSource(pbr_shader.ConnectableAPI(), "surface")
return material
def create_textured_board(stage, prim_path, width, height, center, euler_rot_deg, usd_material):
mesh = UsdGeom.Mesh.Define(stage, prim_path)
w, h = width / 2.0, height / 2.0
mesh.GetPointsAttr().Set(Vt.Vec3fArray([Gf.Vec3f(-w, -h, 0), Gf.Vec3f( w, -h, 0), Gf.Vec3f( w, h, 0), Gf.Vec3f(-w, h, 0)]))
mesh.GetFaceVertexCountsAttr().Set([4])
mesh.GetFaceVertexIndicesAttr().Set([0, 1, 2, 3])
mesh.GetNormalsAttr().Set([Gf.Vec3f(0, 0, 1)] * 4)
mesh.SetNormalsInterpolation(UsdGeom.Tokens.vertex)
primvars_api = UsdGeom.PrimvarsAPI(mesh)
st_primvar = primvars_api.CreatePrimvar("st", Sdf.ValueTypeNames.TexCoord2fArray, UsdGeom.Tokens.vertex)
st_primvar.Set([Gf.Vec2f(0, 0), Gf.Vec2f(1, 0), Gf.Vec2f(1, 1), Gf.Vec2f(0, 1)])
mesh.GetExtentAttr().Set([Gf.Vec3f(-w, -h, -0.01), Gf.Vec3f(w, h, 0.01)])
xform = UsdGeom.Xformable(mesh)
xform.AddTranslateOp().Set(Gf.Vec3d(*center))
xform.AddRotateXYZOp().Set(Gf.Vec3f(*euler_rot_deg))
UsdShade.MaterialBindingAPI.Apply(mesh.GetPrim()).Bind(usd_material)
return mesh
def build_workshop():
world = World(stage_units_in_meters=1.0)
L, W, H, T = 10.0, 6.0, 3.5, 0.2
floor_color = np.array([0.2, 0.2, 0.2])
wall_color = np.array([0.8, 0.8, 0.8])
world.scene.add(FixedCuboid(prim_path="/World/Workshop/Floor", name="floor", position=np.array([0, 0, -T/2]), scale=np.array([L + 2*T, W + 2*T, T]), color=floor_color))
world.scene.add(FixedCuboid(prim_path="/World/Workshop/Ceiling", name="ceiling", position=np.array([0, 0, H + T/2]), scale=np.array([L + 2*T, W + 2*T, T]), color=wall_color))
world.scene.add(FixedCuboid(prim_path="/World/Workshop/Wall_Front", name="wall_front", position=np.array([L/2 + T/2, 0, H/2]), scale=np.array([T, W, H]), color=wall_color))
world.scene.add(FixedCuboid(prim_path="/World/Workshop/Wall_Back", name="wall_back", position=np.array([-L/2 - T/2, 0, H/2]), scale=np.array([T, W, H]), color=wall_color))
world.scene.add(FixedCuboid(prim_path="/World/Workshop/Wall_Left", name="wall_left", position=np.array([0, W/2 + T/2, H/2]), scale=np.array([L + 2*T, T, H]), color=wall_color))
world.scene.add(FixedCuboid(prim_path="/World/Workshop/Wall_Right", name="wall_right", position=np.array([0, -W/2 - T/2, H/2]), scale=np.array([L + 2*T, T, H]), color=wall_color))
light_positions = [(L/4, W/4, H - 0.5), (L/4, -W/4, H - 0.5), (-L/4, W/4, H - 0.5), (-L/4, -W/4, H - 0.5)]
for i, pos in enumerate(light_positions):
create_prim(prim_path=f"/World/Workshop/Lights/Light_{i}", prim_type="SphereLight", position=np.array(pos), attributes={"inputs:radius": 0.3, "inputs:intensity": 30000.0, "inputs:color": (1.0, 1.0, 0.95)})
cb_rows, cb_cols = 6, 9
cb_square_size = 0.20
tex_path = create_checkerboard_image("checkerboard.png", rows=cb_rows, cols=cb_cols, square_size_px=500)
stage = omni.usd.get_context().get_stage()
mat_path = "/World/Workshop/Materials/CheckerboardMat"
usd_material = create_raw_usd_material(stage, mat_path, tex_path)
board_w = (cb_cols + 2) * cb_square_size
board_h = (cb_rows + 2) * cb_square_size
z_height = H / 2.0
offset = 0.05
board_configs = [
("/World/Workshop/CalibrationBoards/Front", [ L/2 - offset, 0, z_height], [90, 0, 90]),
("/World/Workshop/CalibrationBoards/Back", [-L/2 + offset, 0, z_height], [90, 0, -90]),
("/World/Workshop/CalibrationBoards/Left", [0, W/2 - offset, z_height], [90, 0, 0]),
("/World/Workshop/CalibrationBoards/Right", [0, -W/2 + offset, z_height], [90, 0, 180])
]
for path, pos, euler_rot in board_configs:
create_textured_board(stage, path, board_w, board_h, pos, euler_rot, usd_material)
camera_z = H - 0.1
camera = Camera(prim_path="/World/Workshop/CalibrationCamera", position=np.array([0.0, 0.0, camera_z]), frequency=20, resolution=(1280, 720))
camera.set_world_pose(orientation=np.array([1.0, 0.0, 0.0, 0.0]))
camera.initialize()
camera.set_focal_length(5.0)
keys = og.Controller.Keys
og.Controller.edit({"graph_path": "/World/ROS2_Camera_Graph", "evaluator_name": "execution"},
{keys.CREATE_NODES: [("OnTick", "omni.graph.action.OnTick"), ("ROS2Camera", "omni.isaac.ros2_bridge.ROS2CameraHelper")],
keys.CONNECT: [("OnTick.outputs:tick", "ROS2Camera.inputs:execIn")],
keys.SET_VALUES: [("ROS2Camera.inputs:renderProductPath", camera.get_render_product_path()), ("ROS2Camera.inputs:topicName", "/AutoCalib_Workshop/camera/image_raw"), ("ROS2Camera.inputs:type", "rgb")]})
add_corner_rotary_lidars(room_length=L, room_width=W, height=H - 0.2, lidar_config="Example_Rotary", topic_prefix="/AutoCalib_Workshop/lidar")
# ================= 【🚗核心新增 1：构建物理层 AGV 底盘】 =================
# 主车体：带质量的物理刚体
# world.scene.add(
# DynamicCuboid(
# prim_path="/World/Workshop/Vehicle", name="agv_vehicle",
# position=np.array([0.0, 0.0, 0.2]), # 中心高度 20cm，完美贴地防穿模
# scale=np.array([0.8, 0.5, 0.3]), # 车辆尺寸：长0.8m x 宽0.5m x 高0.3m
# color=np.array([0.2, 0.6, 1.0]), # 亮蓝色车身
# mass=50.0 # 赋予 50kg 的真实物理质量
# )
# )
# 车头指示器：红色方块，挂载在车头正前方，明确指示 +X 前进方向
# VisualCuboid(
# prim_path="/World/Workshop/Vehicle/DirectionMarker",
# name="direction_marker",
# position=np.array([0.4, 0.0, 0.0]), # 相对车身局部前移
# scale=np.array([0.1, 0.51, 0.31]),
# color=np.array([1.0, 0.0, 0.0]) # 直接通过内置的 color 参数设置
# )
# ================= 【🚗核心新增 1：导入真实 URDF 替换基础方块】 =================
urdf_file_path = "/home/nvidia/study/AutoCalib-Workshop/models/ack_m.urdf"
# 🚨 新增：指定转换后的 USD 文件保存在哪里（必须带 .usd 后缀）
dest_usd_path = "/home/nvidia/study/AutoCalib-Workshop/models/ack_m.usd"
dest_prim_path = "/World/Workshop/Vehicle"
# 1. 配置 URDF 导入参数
import_config = _urdf.ImportConfig()
import_config.merge_fixed_joints = True # 🚨 关键修改：改为 True！将雷达、相机和空节点合并进主车身
import_config.convex_decomp = False
import_config.fix_base = False
import_config.make_default_prim = True
# 2. 将 URDF 解析并保存为本地的 USD 文件
omni.kit.commands.execute(
"URDFParseAndImportFile",
urdf_path=urdf_file_path,
import_config=import_config,
dest_path=dest_usd_path # 传入的是硬盘文件路径
)
# 3. 🔥 将硬盘上的 USD 文件作为引用（Reference）挂载到场景树中
add_reference_to_stage(usd_path=dest_usd_path, prim_path=dest_prim_path)
# 4. 包装为 Robot 对象
world.scene.add(
Robot(
prim_path=dest_prim_path,
name="agv_vehicle",
position=np.array([0.0, 0.0, 0.05])
)
)
# ========================================================================================
# 强制关闭物理引擎对车辆的“休眠优化(Sleep)”，确保它随时能被指令叫醒移动
physx_rb = PhysxSchema.PhysxRigidBodyAPI.Get(stage, "/World/Workshop/Vehicle")
if physx_rb:
physx_rb.GetSleepThresholdAttr().Set(0.0)
# ================= 【🚗核心新增 2：无缝底层 Twist 订阅图】 =================
og.Controller.edit({"graph_path": "/World/ROS2_Twist_Graph", "evaluator_name": "execution"},
{
keys.CREATE_NODES: [
("OnTick", "omni.graph.action.OnTick"),
("TwistSub", "omni.isaac.ros2_bridge.ROS2SubscribeTwist"), # <--- 已修正
],
keys.CONNECT: [
("OnTick.outputs:tick", "TwistSub.inputs:execIn"),
],
keys.SET_VALUES: [
("TwistSub.inputs:topicName", "/cmd_vel"),
]
})
# ========================================================================================
return world
def main():
world = build_workshop()
world.reset()
# 上帝视角的俯视监控
set_camera_view(eye=np.array([0.001, 0.0, 3.4]), target=np.array([0.0, 0.0, 0.0]))
print("======================================================")
print(" 🎯 标定车间完美运行！全向 AGV (蓝身红头) 已就绪！")
print(" ---------------------------------------------------")
print(" 🎮 车辆控制指南：请打开您的**原生终端** (不激活 conda)，输入:")
print(" ros2 topic pub /cmd_vel geometry_msgs/msg/Twist \"{linear: {x: 0.5}, angular: {z: 0.8}}\"")
print("======================================================")
agv = world.scene.get_object("agv_vehicle")
while simulation_app.is_running():
# ================= 【🚗核心闭环：实时提取 Twist，转换物理运动学】 =================
try:
# 1. 每一帧从底层 ActionGraph 中拉取解包出来的 ROS2 速度指令
lin_vel = og.Controller.get(og.Controller.attribute("/World/ROS2_Twist_Graph/TwistSub.outputs:linearVelocity"))
ang_vel = og.Controller.get(og.Controller.attribute("/World/ROS2_Twist_Graph/TwistSub.outputs:angularVelocity"))
if lin_vel is not None and ang_vel is not None and len(lin_vel) == 3:
# 2. 获取车辆在物理世界中实时的绝对姿态四元数 [w, x, y, z] 和 自然下落速度
pos, quat = agv.get_world_pose()
curr_lin_vel = agv.get_linear_velocity()
# 3. 构造 3D 四元数和旋转矩阵
q = Gf.Quatd(float(quat[0]), float(quat[1]), float(quat[2]), float(quat[3]))
rot_mat = Gf.Matrix3d(Gf.Rotation(q))
# 🚨 核心修复：USD (pxr.Gf) 中，向量与矩阵相乘直接使用 * 运算符（行向量右乘矩阵）
world_lin_vel = Gf.Vec3d(*lin_vel) * rot_mat
world_ang_vel = Gf.Vec3d(*ang_vel) * rot_mat
# 4. 物理防翻车约束
target_lin_vel = np.array([world_lin_vel[0], world_lin_vel[1], curr_lin_vel[2]])
target_ang_vel = np.array([0.0, 0.0, world_ang_vel[2]])
# 5. 直接对车辆物理质心施加强制推演覆盖
agv.set_linear_velocity(target_lin_vel)
agv.set_angular_velocity(target_ang_vel)
# Debug 日志：确认 ROS2 话题是否真正连通
if abs(lin_vel[0]) > 0.01 or abs(ang_vel[2]) > 0.01:
print(f"\r[ROS2 Debug] 车辆移动中: 线速度 {lin_vel[0]:.2f}, 角速度 {ang_vel[2]:.2f}", end="")
except Exception as e:
# 🚨 永远不要用 pass 吞掉这里的报错
print(f"\n[ERROR] 运动学控制循环异常: {e}")
# ============================================================================================
world.step(render=True)
simulation_app.close()
if __name__ == "__main__":
main()