基本单位：
长度 米
质量 千克
时间 秒
电流 安培
导出单位
角度 弧度
频率 赫兹
力 牛顿
功率 瓦特
电压 伏特
温度 摄氏度
磁感应强度 特斯拉
坐标系约定
In relation to a body the standard is:
- x forward
- y left
- z up
For short-range Cartesian representations of geographic locations, use the ENU convention:
- X east
- Y north
- Z up
后缀框架
In the case of cameras, there is often a second frame defined with a "_optical" suffix. This uses a slightly different convention:
- z forward
- x right
- y down
For outdoor systems where it is desireable to work under the north east down [6] (NED) convention, define an appropriately transformed secondary frame with the "_ned" suffix:
- X north
- Y east
- Z down
旋转表示
There are many ways to represent rotations. The preferred order is listed below, along with rationale.
- quaternion
- Compact representation
- No singularities
- rotation matrix
- No singularities
- fixed axis roll, pitch, yaw about X, Y, Z axes respectively
- No ambiguity on order
- Used for angular velocities
- euler angles yaw, pitch, and roll about Z, Y, X axes respectively
- Euler angles are generally discouraged due to having 24 ‘valid‘ conventions with different domains using different conventions by default.
By the right hand rule, the yaw component of orientation increases as the child frame rotates counter-clockwise, and for geographic poses, yaw is zero when pointing east.
This requires special mention only because it differs from a traditional compass bearing, which is zero when pointing north and increments clockwise. Hardware drivers should make the appropriate transformations before publishing standard ROS messages.
协方差表示
Linear
float64[9] linear_acceleration_covariance # 3x3 row major matrix in x, y, z order
Angular
float64[9] angular_velocity_covariance # 3x3 row major matrix about x, y, z order with fixed axes
Six Dimensional
# Row-major representation of the 6x6 covariance matrix # The orientation parameters use a fixed-axis representation. # In order, the parameters are: # (x, y, z, rotation about X axis, rotation about Y axis, rotation about Z axis) float64[36] covariance