首先，我使用的是 v1.0 版本，宇樹最近發力了更新的很快：xr_teleoperate-1.0

teleop_hand_and_arm.py 支持通過 XR 設備（比如手勢或手柄）來控制實際機器人動作，也支持在虛擬仿真中運行。可以根據需要，通過命令行參數來配置運行方式

啟動參數說明：

?1. 基礎控制參數

?2. 模式開關參數

選擇手勢跟蹤來控制 G1(29 DoF) + inspire1 靈巧手設備，同時開啟數據錄制模式，則啟動命令如下所示（建議在 terminal 中運行）：

python teleop_hand_and_arm.py --xr-mode=hand --arm=G1_29 --ee=inspire1 --record --motion

接下來詳細分析一下這個腳本，這個腳本高度模塊化，可擴展性極好，并且采用并發設計，可以做很多二開

目錄

1 腳本解析

1.1?導入依賴及路徑配置

1.2?仿真控制輔助函數

1.3?全局狀態管理與鍵盤監聽回調

1.4?主函數入口與參數解析

1.5?圖像通道配置與共享內存初始化

1.6 XR/手勢與機器人運動控制綁定

1.7 仿真與運動客戶端初始化

1.8?主循環 - 控制、記錄與交互核心

1.9?異常處理與資源清理

2 相機適配與腳本測試

2.1 相機適配

2.2 腳本測試

2.1?圖像服務

2.2 主控腳本測試

1 腳本解析

1.1?導入依賴及路徑配置

import numpy as np  # 科學計算庫，主要用于矩陣、圖像等數據處理
import time         # 提供時間和延遲函數
import argparse     # 用于命令行參數解析
import cv2          # OpenCV，常用于圖像處理和顯示
from multiprocessing import shared_memory, Value, Array, Lock  # 多進程數據共享和同步
import threading    # 多線程，用于異步任務如鍵盤監聽、圖像接收
import logging_mp   # 自定義多進程日志模塊，便于跨進程日志收集
logging_mp.basic_config(level=logging_mp.INFO)  # 設置日志等級為INFO
logger_mp = logging_mp.get_logger(__name__)     # 獲取當前模塊的日志實例import os           # 操作系統相關
import sys          # 系統參數和函數
current_dir = os.path.dirname(os.path.abspath(__file__))  # 當前腳本所在目錄
parent_dir = os.path.dirname(current_dir)                 # 上級目錄（項目根目錄）
sys.path.append(parent_dir)                               # 把根目錄加入模塊搜索路徑，便于import自定義模塊# 導入自定義功能模塊
from televuer import TeleVuerWrapper    # XR/VR交互與手勢、相機接口
from teleop.robot_control.robot_arm import G1_29_ArmController, G1_23_ArmController, H1_2_ArmController, H1_ArmController   # 手臂控制器
from teleop.robot_control.robot_arm_ik import G1_29_ArmIK, G1_23_ArmIK, H1_2_ArmIK, H1_ArmIK   # 手臂逆解算器
from teleop.robot_control.robot_hand_unitree import Dex3_1_Controller, Gripper_Controller      # Unitree手/夾爪控制器
from teleop.robot_control.robot_hand_inspire import Inspire_Controller                         # Inspire手控制器
from teleop.image_server.image_client import ImageClient    # 遠程圖像采集客戶端
from teleop.utils.episode_writer import EpisodeWriter       # episode數據記錄器
from sshkeyboard import listen_keyboard, stop_listening     # 跨平臺鍵盤監聽，非阻塞# 仿真相關：Isaac通信話題
from unitree_sdk2py.core.channel import ChannelPublisher    # DDS通信話題發布器
from unitree_sdk2py.idl.std_msgs.msg.dds_ import String_    # 通用字符串消息類型

• televuer：XR/VR端的手勢、頭顯追蹤數據與畫面交互橋
• robot_control：控制不同型號手臂和末端執行器
• episode_writer：用于實驗數據記錄和存檔
• ImageClient：用于與遠端攝像頭畫面服務器通信
• sshkeyboard：跨平臺鍵盤監聽

1.2?仿真控制輔助函數

def publish_reset_category(category: int, publisher):       # 發布仿真場景重置信號msg = String_(data=str(category))                      # 構造消息publisher.Write(msg)                                   # 發布logger_mp.info(f"published reset category: {category}")# 日志記錄

向 Isaac 仿真環境發布場景重置信號，便于環境回溯、重新初始化

1.3?全局狀態管理與鍵盤監聽回調

# 全局運行狀態變量
start_signal = False        # 標志是否開始主循環（r鍵觸發）
running = True              # 主循環運行標志
should_toggle_recording = False   # 是否切換錄制狀態（s鍵觸發）
is_recording = False        # 當前是否處于錄制狀態def on_press(key):          # 鍵盤按下回調global running, start_signal, should_toggle_recordingif key == 'r':                  # 'r'鍵：啟動主循環start_signal = Truelogger_mp.info("Program start signal received.")elif key == 'q':                # 'q'鍵：退出主循環stop_listening()running = Falseelif key == 's':                # 's'鍵：切換錄制should_toggle_recording = Trueelse:logger_mp.info(f"{key} was pressed, but no action is defined for this key.")# 啟動鍵盤監聽線程，監聽過程中不會阻塞主線程
listen_keyboard_thread = threading.Thread(target=listen_keyboard, kwargs={"on_press": on_press, "until": None, "sequential": False,},daemon=True
)
listen_keyboard_thread.start()  # 啟動監聽

• 維護主狀態機（是否運行、是否錄制等），通過鍵盤控制流程轉移（r:開始；q:退出；s:切換錄制）
• listen_keyboard_thread：監聽線程，用于實現用戶無阻塞交互

1.4?主函數入口與參數解析

if __name__ == '__main__':   # 程序主入口parser = argparse.ArgumentParser()   # 創建參數解析器parser.add_argument('--task_dir', type=str, default='./utils/data', help='path to save data')  # 數據保存路徑parser.add_argument('--frequency', type=float, default=90.0, help="save data's frequency")     # 采樣頻率parser.add_argument('--xr-mode', type=str, choices=['hand', 'controller'], default='hand', help='Select XR device tracking source') # XR輸入模式parser.add_argument('--arm', type=str, choices=['G1_29', 'G1_23', 'H1_2', 'H1'], default='G1_29', help='Select arm controller')      # 選用手臂parser.add_argument('--ee', type=str, choices=['dex3', 'gripper', 'inspire1'], help='Select end effector controller')               # 末端類型parser.add_argument('--record', action='store_true', help='Enable data recording')           # 是否錄制數據parser.add_argument('--motion', action='store_true', help='Enable motion control mode')      # 是否開啟運動模式parser.add_argument('--headless', action='store_true', help='Enable headless mode (no display)') # 是否無頭（無窗口）模式parser.add_argument('--sim', action='store_true', help='Enable isaac simulation mode')       # 是否仿真args = parser.parse_args()         # 解析參數logger_mp.info(f"args: {args}")    # 輸出參數配置

命令行參數管理，支持靈活配置，如：數據路徑、幀率、手臂類型、末端類型、是否仿真、是否錄制、是否無頭模式等

1.5?圖像通道配置與共享內存初始化

    # -------- 圖像客戶端/共享內存配置 --------if args.sim:  # 仿真配置img_config = {'fps': 30,'head_camera_type': 'opencv','head_camera_image_shape': [480, 640],    # 頭部相機分辨率'head_camera_id_numbers': [0],'wrist_camera_type': 'opencv','wrist_camera_image_shape': [480, 640],   # 腕部相機分辨率'wrist_camera_id_numbers': [2, 4],}else:         # 實機配置img_config = {'fps': 30,'head_camera_type': 'opencv','head_camera_image_shape': [480, 1280],   # 頭部相機分辨率（1280更寬，可能雙目）'head_camera_id_numbers': [0],'wrist_camera_type': 'opencv','wrist_camera_image_shape': [480, 640],'wrist_camera_id_numbers': [2, 4],}ASPECT_RATIO_THRESHOLD = 2.0  # 判別雙目/單目的分辨率閾值# 判斷是否為雙目頭相機if len(img_config['head_camera_id_numbers']) > 1 or (img_config['head_camera_image_shape'][1] / img_config['head_camera_image_shape'][0] > ASPECT_RATIO_THRESHOLD):BINOCULAR = Trueelse:BINOCULAR = False# 是否有腕部相機if 'wrist_camera_type' in img_config:WRIST = Trueelse:WRIST = False# 設置頭部相機的共享內存圖像shapeif BINOCULAR and not (img_config['head_camera_image_shape'][1] / img_config['head_camera_image_shape'][0] > ASPECT_RATIO_THRESHOLD):tv_img_shape = (img_config['head_camera_image_shape'][0], img_config['head_camera_image_shape'][1] * 2, 3)else:tv_img_shape = (img_config['head_camera_image_shape'][0], img_config['head_camera_image_shape'][1], 3)# 申請頭部相機的共享內存，并映射為numpy數組tv_img_shm = shared_memory.SharedMemory(create=True, size=np.prod(tv_img_shape) * np.uint8().itemsize)tv_img_array = np.ndarray(tv_img_shape, dtype=np.uint8, buffer=tv_img_shm.buf)# 腕部相機同理，判斷WRIST和仿真，創建對應的共享內存和客戶端if WRIST and args.sim:wrist_img_shape = (img_config['wrist_camera_image_shape'][0], img_config['wrist_camera_image_shape'][1] * 2, 3)wrist_img_shm = shared_memory.SharedMemory(create=True, size=np.prod(wrist_img_shape) * np.uint8().itemsize)wrist_img_array = np.ndarray(wrist_img_shape, dtype=np.uint8, buffer=wrist_img_shm.buf)img_client = ImageClient(tv_img_shape=tv_img_shape, tv_img_shm_name=tv_img_shm.name, wrist_img_shape=wrist_img_shape, wrist_img_shm_name=wrist_img_shm.name, server_address="127.0.0.1")elif WRIST and not args.sim:wrist_img_shape = (img_config['wrist_camera_image_shape'][0], img_config['wrist_camera_image_shape'][1] * 2, 3)wrist_img_shm = shared_memory.SharedMemory(create=True, size=np.prod(wrist_img_shape) * np.uint8().itemsize)wrist_img_array = np.ndarray(wrist_img_shape, dtype=np.uint8, buffer=wrist_img_shm.buf)img_client = ImageClient(tv_img_shape=tv_img_shape, tv_img_shm_name=tv_img_shm.name, wrist_img_shape=wrist_img_shape, wrist_img_shm_name=wrist_img_shm.name)else:  # 沒有腕部相機，僅頭部相機img_client = ImageClient(tv_img_shape=tv_img_shape, tv_img_shm_name=tv_img_shm.name)# 圖像接收線程，持續將遠程圖像寫入共享內存image_receive_thread = threading.Thread(target=img_client.receive_process, daemon=True)image_receive_thread.daemon = Trueimage_receive_thread.start()

• 兼容多相機（頭、腕）、多分辨率與雙目/單目場景

• 用共享內存高效實現多進程（如圖像采集與主控）之間的數據高速傳遞，保證零拷貝

• 圖像客戶端單獨線程異步接收，保證主線程不卡頓

1.6 XR/手勢與機器人運動控制綁定

    # XR橋接實例，負責手勢/動作/圖像數據交互tv_wrapper = TeleVuerWrapper(binocular=BINOCULAR, use_hand_tracking=args.xr_mode == 'hand',img_shape=tv_img_shape, img_shm_name=tv_img_shm.name, return_state_data=True, return_hand_rot_data=False)# -------- 機器人臂、末端控制器與逆運動學模塊加載 --------if args.arm == 'G1_29':arm_ctrl = G1_29_ArmController(motion_mode=args.motion, simulation_mode=args.sim)arm_ik = G1_29_ArmIK()elif args.arm == 'G1_23':arm_ctrl = G1_23_ArmController(simulation_mode=args.sim)arm_ik = G1_23_ArmIK()elif args.arm == 'H1_2':arm_ctrl = H1_2_ArmController(simulation_mode=args.sim)arm_ik = H1_2_ArmIK()elif args.arm == 'H1':arm_ctrl = H1_ArmController(simulation_mode=args.sim)arm_ik = H1_ArmIK()# -------- 末端執行器控制器/數據區初始化 --------if args.ee == "dex3":  # 雙Dex3機械手left_hand_pos_array = Array('d', 75, lock=True)      # 左手輸入 75維right_hand_pos_array = Array('d', 75, lock=True)     # 右手輸入 75維dual_hand_data_lock = Lock()                         # 雙手輸入鎖dual_hand_state_array = Array('d', 14, lock=False)   # 輸出當前左右手statedual_hand_action_array = Array('d', 14, lock=False)  # 輸出當前左右手actionhand_ctrl = Dex3_1_Controller(left_hand_pos_array, right_hand_pos_array, dual_hand_data_lock,dual_hand_state_array, dual_hand_action_array)elif args.ee == "gripper":  # 雙夾爪left_gripper_value = Value('d', 0.0, lock=True)      # 左夾爪輸入right_gripper_value = Value('d', 0.0, lock=True)     # 右夾爪輸入dual_gripper_data_lock = Lock()                      # 夾爪同步鎖dual_gripper_state_array = Array('d', 2, lock=False) # 輸出當前左右夾爪statedual_gripper_action_array = Array('d', 2, lock=False)# 輸出當前左右夾爪actiongripper_ctrl = Gripper_Controller(left_gripper_value, right_gripper_value, dual_gripper_data_lock,dual_gripper_state_array, dual_gripper_action_array, simulation_mode=args.sim)elif args.ee == "inspire1":  # Inspire手left_hand_pos_array = Array('d', 75, lock=True)      # Inspire手輸入right_hand_pos_array = Array('d', 75, lock=True)dual_hand_data_lock = Lock()dual_hand_state_array = Array('d', 12, lock=False)dual_hand_action_array = Array('d', 12, lock=False)hand_ctrl = Inspire_Controller(left_hand_pos_array, right_hand_pos_array, dual_hand_data_lock,dual_hand_state_array, dual_hand_action_array)else:pass  # 沒選末端則跳過

• XR 設備（如 Apple Vision）追蹤的數據，通過?tv_wrapper 進行抽象和接口化，統一管理
• 根據參數，靈活加載目標機器人的運動學與執行器控制（如 7/6軸、Dex3、夾爪等）

1.7 仿真與運動客戶端初始化

    # -------- 仿真相關初始化 --------if args.sim:reset_pose_publisher = ChannelPublisher("rt/reset_pose/cmd", String_)  # 創建仿真重置話題reset_pose_publisher.Init()                                            # 初始化from teleop.utils.sim_state_topic import start_sim_state_subscribe     # 仿真狀態訂閱sim_state_subscriber = start_sim_state_subscribe()# -------- 控制器運動模式初始化 --------if args.xr_mode == 'controller' and args.motion:from unitree_sdk2py.g1.loco.g1_loco_client import LocoClientsport_client = LocoClient()sport_client.SetTimeout(0.0001)  # 設置通信超時sport_client.Init()# -------- 數據錄制器初始化 --------if args.record and args.headless:recorder = EpisodeWriter(task_dir=args.task_dir, frequency=args.frequency, rerun_log=False)   # 無頭模式：不復現elif args.record and not args.headless:recorder = EpisodeWriter(task_dir=args.task_dir, frequency=args.frequency, rerun_log=True)    # GUI模式：可復現

• 仿真/實機自適應

• 數據記錄支持無頭與 GUI 兩種模式（適配遠程部署/本地實驗）

• LocoClient 用于高層次運動控制

1.8?主循環 - 控制、記錄與交互核心

    try:logger_mp.info("Please enter the start signal (enter 'r' to start the subsequent program)")# 等待用戶按下 'r' 啟動程序while not start_signal:time.sleep(0.01)arm_ctrl.speed_gradual_max()   # 啟動時速度梯度最大化，安全啟動while running:                 # 主循環，按frequency頻率循環start_time = time.time()if not args.headless:      # 非無頭模式，顯示主畫面tv_resized_image = cv2.resize(tv_img_array, (tv_img_shape[1] // 2, tv_img_shape[0] // 2))cv2.imshow("record image", tv_resized_image)key = cv2.waitKey(1) & 0xFFif key == ord('q'):stop_listening()running = Falseif args.sim:publish_reset_category(2, reset_pose_publisher)elif key == ord('s'):should_toggle_recording = Trueelif key == ord('a'):if args.sim:publish_reset_category(2, reset_pose_publisher)if args.record and should_toggle_recording:should_toggle_recording = Falseif not is_recording:if recorder.create_episode():is_recording = Trueelse:logger_mp.error("Failed to create episode. Recording not started.")else:is_recording = Falserecorder.save_episode()if args.sim:publish_reset_category(1, reset_pose_publisher)# 獲取XR/VR動作輸入tele_data = tv_wrapper.get_motion_state_data()# 不同末端/輸入模式下的輸入數據賦值if (args.ee == 'dex3' or args.ee == 'inspire1') and args.xr_mode == 'hand':with left_hand_pos_array.get_lock():left_hand_pos_array[:] = tele_data.left_hand_pos.flatten()with right_hand_pos_array.get_lock():right_hand_pos_array[:] = tele_data.right_hand_pos.flatten()elif args.ee == 'gripper' and args.xr_mode == 'controller':with left_gripper_value.get_lock():left_gripper_value.value = tele_data.left_trigger_valuewith right_gripper_value.get_lock():right_gripper_value.value = tele_data.right_trigger_valueelif args.ee == 'gripper' and args.xr_mode == 'hand':with left_gripper_value.get_lock():left_gripper_value.value = tele_data.left_pinch_valuewith right_gripper_value.get_lock():right_gripper_value.value = tele_data.right_pinch_valueelse:pass        # 高級運動控制（如遙控器模式）if args.xr_mode == 'controller' and args.motion:# 右A鍵退出if tele_data.tele_state.right_aButton:running = False# 左右搖桿共同按下，減震模式（緊急停止）if tele_data.tele_state.left_thumbstick_state and tele_data.tele_state.right_thumbstick_state:sport_client.Damp()# 運動控制，速度限制在0.3以內sport_client.Move(-tele_data.tele_state.left_thumbstick_value[1] * 0.3,-tele_data.tele_state.left_thumbstick_value[0] * 0.3,-tele_data.tele_state.right_thumbstick_value[0] * 0.3)# 獲取當前雙臂關節狀態和速度current_lr_arm_q  = arm_ctrl.get_current_dual_arm_q()current_lr_arm_dq = arm_ctrl.get_current_dual_arm_dq()# 求逆解得到目標關節和力矩time_ik_start = time.time()sol_q, sol_tauff  = arm_ik.solve_ik(tele_data.left_arm_pose, tele_data.right_arm_pose,current_lr_arm_q, current_lr_arm_dq)time_ik_end = time.time()logger_mp.debug(f"ik:\t{round(time_ik_end - time_ik_start, 6)}")# 控制機械臂arm_ctrl.ctrl_dual_arm(sol_q, sol_tauff)# ------ 數據錄制流程 ------if args.record:# 各種末端/模式下狀態和動作的收集與組織if args.ee == "dex3" and args.xr_mode == 'hand':with dual_hand_data_lock:left_ee_state = dual_hand_state_array[:7]right_ee_state = dual_hand_state_array[-7:]left_hand_action = dual_hand_action_array[:7]right_hand_action = dual_hand_action_array[-7:]current_body_state = []current_body_action = []elif args.ee == "gripper" and args.xr_mode == 'hand':with dual_gripper_data_lock:left_ee_state = [dual_gripper_state_array[1]]right_ee_state = [dual_gripper_state_array[0]]left_hand_action = [dual_gripper_action_array[1]]right_hand_action = [dual_gripper_action_array[0]]current_body_state = []current_body_action = []elif args.ee == "gripper" and args.xr_mode == 'controller':with dual_gripper_data_lock:left_ee_state = [dual_gripper_state_array[1]]right_ee_state = [dual_gripper_state_array[0]]left_hand_action = [dual_gripper_action_array[1]]right_hand_action = [dual_gripper_action_array[0]]current_body_state = arm_ctrl.get_current_motor_q().tolist()current_body_action = [-tele_data.tele_state.left_thumbstick_value[1]  * 0.3,-tele_data.tele_state.left_thumbstick_value[0]  * 0.3,-tele_data.tele_state.right_thumbstick_value[0] * 0.3]elif args.ee == "inspire1" and args.xr_mode == 'hand':with dual_hand_data_lock:left_ee_state = dual_hand_state_array[:6]right_ee_state = dual_hand_state_array[-6:]left_hand_action = dual_hand_action_array[:6]right_hand_action = dual_hand_action_array[-6:]current_body_state = []current_body_action = []else:left_ee_state = []right_ee_state = []left_hand_action = []right_hand_action = []current_body_state = []current_body_action = []# 圖像采集current_tv_image = tv_img_array.copy()if WRIST:current_wrist_image = wrist_img_array.copy()# 關節狀態/動作left_arm_state  = current_lr_arm_q[:7]right_arm_state = current_lr_arm_q[-7:]left_arm_action = sol_q[:7]right_arm_action = sol_q[-7:]if is_recording:colors = {}depths = {}# 多相機/雙目數據分流if BINOCULAR:colors[f"color_{0}"] = current_tv_image[:, :tv_img_shape[1]//2]colors[f"color_{1}"] = current_tv_image[:, tv_img_shape[1]//2:]if WRIST:colors[f"color_{2}"] = current_wrist_image[:, :wrist_img_shape[1]//2]colors[f"color_{3}"] = current_wrist_image[:, wrist_img_shape[1]//2:]else:colors[f"color_{0}"] = current_tv_imageif WRIST:colors[f"color_{1}"] = current_wrist_image[:, :wrist_img_shape[1]//2]colors[f"color_{2}"] = current_wrist_image[:, wrist_img_shape[1]//2:]# 組織各類狀態states = {"left_arm": {                                                                    "qpos":   left_arm_state.tolist(),    # 關節角度"qvel":   [],                          "torque": [],                        }, "right_arm": {                                                                    "qpos":   right_arm_state.tolist(),       "qvel":   [],                          "torque": [],                         },                        "left_ee": {                                                                    "qpos":   left_ee_state,           "qvel":   [],                           "torque": [],                          }, "right_ee": {                                                                    "qpos":   right_ee_state,       "qvel":   [],                           "torque": [],  }, "body": {"qpos": current_body_state,}, }actions = {"left_arm": {                                   "qpos":   left_arm_action.tolist(),       "qvel":   [],       "torque": [],      }, "right_arm": {                                   "qpos":   right_arm_action.tolist(),       "qvel":   [],       "torque": [],       },                         "left_ee": {                                   "qpos":   left_hand_action,       "qvel":   [],       "torque": [],       }, "right_ee": {                                   "qpos":   right_hand_action,       "qvel":   [],       "torque": [], }, "body": {"qpos": current_body_action,}, }if args.sim:  # 仿真狀態同時錄制sim_state = sim_state_subscriber.read_data()            recorder.add_item(colors=colors, depths=depths, states=states, actions=actions, sim_state=sim_state)else:recorder.add_item(colors=colors, depths=depths, states=states, actions=actions)# 控制主循環幀率（frequency控制，每周期做sleep補償）current_time = time.time()time_elapsed = current_time - start_timesleep_time = max(0, (1 / args.frequency) - time_elapsed)time.sleep(sleep_time)logger_mp.debug(f"main process sleep: {sleep_time}")

• 核心循環依賴于全局狀態管理，控制整體流程啟動、結束、錄制等邏輯

• 通過 XR 設備采集動作/手勢數據，結合當前機器人狀態，實時求逆解控制

• 支持仿真和實機的兼容、數據分流、錄制、UI 預覽等功能

• 按設置頻率同步主循環（保持控制與采樣一致性）

1.9?異常處理與資源清理

    except KeyboardInterrupt:logger_mp.info("KeyboardInterrupt, exiting program...")  # 捕獲Ctrl+C優雅退出finally:arm_ctrl.ctrl_dual_arm_go_home()     # 程序結束時歸位if args.sim:sim_state_subscriber.stop_subscribe()tv_img_shm.close()tv_img_shm.unlink()if WRIST:wrist_img_shm.close()wrist_img_shm.unlink()if args.record:recorder.close()listen_keyboard_thread.join()logger_mp.info("Finally, exiting program...")exit(0)

• 保證即使中斷也能自動歸位/釋放機器人

• 關閉所有共享內存、線程、數據記錄器，防止資源泄露

2 相機適配與腳本測試

目前官方給的遙操作是另外一套相機：

宇樹各個模塊參考鏈接：https://github.com/unitreerobotics/xr_teleoperate?tab=readme-ov-file

宇樹相機參考鏈接：[For reference only]?http://e.tb.cn/h.TaZxgkpfWkNCakg?tk=KKz03Kyu04u

為了與官方測試最為相機，我采用的是 “120無畸變”

先記一下這個相機的適配過程

2.1 相機適配

1.?使用 v4l2-ctl 命令預覽設備信息

首先可以確認相機設備確實存在并可以訪問：

v4l2-ctl --list-devices

或直接查看格式和分辨率支持：

v4l2-ctl --device=/dev/video6 --list-formats-ext
v4l2-ctl --device=/dev/video7 --list-formats-ext

2. 使用 ffplay 快速查看

ffplay /dev/video6

如果沒有 ffplay，先裝一下：sudo apt install ffmpeg

3. 使用 opencv 腳本查看

寫一個簡單的腳本：

'''
#雙目
import cv2cap = cv2.VideoCapture(0)
while True:ret, frame = cap.read()if not ret:break# 雙目拆分（假設1280x480，左右各640x480）left = frame[:, :frame.shape[1]//2]right = frame[:, frame.shape[1]//2:]cv2.imshow('left', left)cv2.imshow('right', right)if cv2.waitKey(1) == ord('q'):break
cap.release()
cv2.destroyAllWindows()
'''#單目
import cv2cap = cv2.VideoCapture(0)
while True:ret, frame = cap.read()if not ret:print("No frame!")breakcv2.imshow("cam6", frame)if cv2.waitKey(1) == ord('q'):break
cap.release()
cv2.destroyAllWindows()

可以顯示：

2.2 腳本測試

2.1?圖像服務

開啟?image_server.py，只需修改 config：

    config = {'fps': 30,'head_camera_type': 'opencv','head_camera_image_shape': [480, 1280],  # Head camera resolution'head_camera_id_numbers': [0],}

然后，新開一個 terminal 開啟 image_client.py，只需修改 ip，具體根據 ifconfig 查看：

client = ImageClient(image_show = True, server_address='192.168.8.30', Unit_Test=False) # deployment test

2.2 主控腳本測試

切記：關掉 client！！！開啟server！！！

如果端口占用就：

#查看進程
sudo lsof -i :8012
#kill 占用端口的進程
sudo kill -9 12345

或者：

sudo kill -9 $(sudo lsof -t -i:8012)

如果報錯 Segment Fault，那就是 dds 通訊沒起來，就添加 cyclonedds 到 ~/.bashrc，然后?source ~/.bashrc?立即生效

export CYCLONEDDS_HOME="/home/unitree/Documents/unitree_sdk2_python/cyclonedds/install"

檢查一下：

echo $CYCLONEDDS_HOME

主控腳本修改 config：

        img_config = {'fps': 30,'head_camera_type': 'opencv','head_camera_image_shape': [480, 1280],  # Head camera resolution'head_camera_id_numbers': [0],}

最后，確保 G1 已經進入?調試模式（L2+R2），并啟動主控腳本：

?

打開瀏覽器應用（ipad Safari 也可以），輸入并訪問網址：https://192.168.8.30:8012?ws=wss://192.168.8.30:8012，可以快樂的遙操作啦

?