sensordata的索引需要依靠mjData的sensor_adr获取,这个可以使用sensor的id
这个我们要注意传感器具有的数据量,有的传感器是一个值,而有的传感器是三个值。我们可以使用mjModel中的sensor_dim获得传感器输出的参数量
演示:
def get_sensor_data(sensor_name):
sensor_id = mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_SENSOR, sensor_name)
if sensor_id == -1:
raise ValueError(f"Sensor '{sensor_name}' not found in model!")
start_idx = m.sensor_adr[sensor_id]
dim = m.sensor_dim[sensor_id]
sensor_values = d.sensordata[start_idx : start_idx + dim]
return sensor_values对于传感器其他的属性在 mjModel中可以直接获得。如下:
现在可以通过 MjData.sensor("sensorname").data 获取传感器数据
相机来源一般是在模型文件中创建相机,或者创建一个相机手动控制,就像 base中 与人交互的画面就是手动创建的相机。我们读取相机的步骤为:
- 初始化glfw
- 创建相机
- 更新场景
- 读取图像
- 通过 opencv将图像转换
MJAPI void mjr_readPixels(unsigned char* rgb, float* depth,
mjrRect viewport, const mjrContext* con);
将渲染画面转成rgb图像和深度图像。 获取相机视角演示: 初始化:
# 初始化glfw
glfw.init()
glfw.window_hint(glfw.VISIBLE,glfw.FALSE)
window = glfw.create_window(1200,900,"mujoco",None,None)
glfw.make_context_current(window)
#创建相机
camera = mujoco.MjvCamera()
camID = mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_CAMERA, "this_camera")
camera.fixedcamid = camID
camera.type = mujoco.mjtCamera.mjCAMERA_FIXED
scene = mujoco.MjvScene(m, maxgeom=1000)
context = mujoco.MjrContext(m, mujoco.mjtFontScale.mjFONTSCALE_150)
mujoco.mjr_setBuffer(mujoco.mjtFramebuffer.mjFB_OFFSCREEN, context)
def get_image(w,h):
# 定义视口大小
viewport = mujoco.MjrRect(0, 0, w, h)
# 更新场景
mujoco.mjv_updateScene(
m, d, mujoco.MjvOption(),
None, camera, mujoco.mjtCatBit.mjCAT_ALL, scene
)
# 渲染到缓冲区
mujoco.mjr_render(viewport, scene, context)
# 读取 RGB 数据(格式为 HWC, uint8)
rgb = np.zeros((h, w, 3), dtype=np.uint8)
mujoco.mjr_readPixels(rgb, None, viewport, context)
cv_image = cv2.cvtColor(np.flipud(rgb), cv2.COLOR_RGB2BGR)
return cv_image获取图像:
def get_image(w,h):
# 定义视口大小
viewport = mujoco.MjrRect(0, 0, w, h)
# 更新场景
mujoco.mjv_updateScene(
m, d, mujoco.MjvOption(),
None, camera, mujoco.mjtCatBit.mjCAT_ALL, scene
)
# 渲染到缓冲区
mujoco.mjr_render(viewport, scene, context)
# 读取 RGB 数据(格式为 HWC, uint8)
rgb = np.zeros((h, w, 3), dtype=np.uint8)
mujoco.mjr_readPixels(rgb, None, viewport, context)
cv_image = cv2.cvtColor(np.flipud(rgb), cv2.COLOR_RGB2BGR)
return cv_image
img = get_image(640,480)
cv2.imshow("img",img)
cv2.waitKey(1)