PointCloud2 标准点云消息格式
- sensor_msgs/PointCloud2.msg
# This message holds a collection of N-dimensional points, which may
# contain additional information such as normals, intensity, etc. The
# point data is stored as a binary blob, its layout described by the
# contents of the "fields" array.
# The point cloud data may be organized 2d (image-like) or 1d
# (unordered). Point clouds organized as 2d images may be produced by
# camera depth sensors such as stereo or time-of-flight.
# Time of sensor data acquisition, and the coordinate frame ID (for 3d
# points).
Header header #文件头
# 2D structure of the point cloud. If the cloud is unordered, height is
# 1 and width is the length of the point cloud.
uint32 height #点云的高度
uint32 width
# Describes the channels and their layout in the binary data blob.
PointField[] fields
bool is_bigendian # Is this data bigendian?
uint32 point_step # Length of a point in bytes
uint32 row_step # Length of a row in bytes
uint8[] data # Actual point data, size is (row_step*height)
bool is_dense # True if there are no invalid points
- std_msgs/Header.msg
# Standard metadata for higher-level stamped data types.
# This is generally used to communicate timestamped data
# in a particular coordinate frame.
#
# sequence ID: consecutively increasing ID
uint32 seq
#Two-integer timestamp that is expressed as:
# * stamp.sec: seconds (stamp_secs) since epoch (in Python the variable is called 'secs')
# * stamp.nsec: nanoseconds since stamp_secs (in Python the variable is called 'nsecs')
# time-handling sugar is provided by the client library
time stamp
#Frame this data is associated with
# 0: no frame
# 1: global frame
string frame_id
官方文档描述
样例数据
header:
seq: 1954
stamp:
secs: 1543839403
nsecs: 303457955
frame_id: "/camera_link"
height: 1
width: 3356
fields:
-
name: "x"
offset: 0
datatype: 7
count: 1
-
name: "y"
offset: 4
datatype: 7
count: 1
-
name: "z"
offset: 8
datatype: 7
count: 1
is_bigendian: False
point_step: 16
row_step: 53696
data: [243, 105, 181, 61, 113, 63, 18, 62, 79, 139, 223, 62, 0, 0, 128, 63, 217, 45, 176, 61, 166, 17, 40, 62, 233, 48, 224, 62, 0, 0, 128, 63, 15, 88, 219, 61, 238, 156, 155, 61, 34, 39, 243, 62, 0, 0, 128, 63, 137, 50,
...
一大堆数字
...
63, 33, 238, 211, 61, 83, 228, 201, 191, 169, 171, 142, 64, 0, 0, 128, 63, 7, 157, 189, 61, 150, 12, 197, 191, 135, 133, 142, 64, 0, 0, 128, 63, 148, 26, 170, 61, 220, 82, 192, 191, 172, 28, 142, 64, 0, 0, 128, 63, 148, 26, 170, 61, 180, 221, 187, 191, 172, 28, 142, 64, 0, 0, 128, 63, 241, 151, 172, 61, 248, 184, 211, 191, 39, 49, 144, 64, 0, 0, 128, 63, 241, 151, 172, 61, 27, 51, 207, 191, 39, 49, 144, 64, 0, 0, 128, 63, 241, 151, 172, 61, 56, 110, 203, 191, 39, 49, 144, 64, 0, 0, 128, 63]
is_dense: True