新增原始数据一步导出到 combined:对齐 Lidar-IMU 导出入口,适配 H32/G90/N300

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
lichun.qu
2026-08-03 16:08:37 +08:00
co-authored by Cursor
parent 24eaa8508e
commit 13624b0be8
14 changed files with 1600 additions and 130 deletions
+371
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@@ -0,0 +1,371 @@
"""Decode RoboSense H32 MSOP V2 .rscap into Cartesian frames (metres).
Angle / distance conventions follow ``RSLidarH32_3D_RawCaptureNet48``:
azimuth = normalize(-(block_az + horizontal[ch])), altitude = vertical[ch],
distance_mm = raw * distance_unit_mm, then:
x = d_m * cos(alt) * cos(az)
y = d_m * cos(alt) * sin(az)
z = d_m * sin(alt)
MSOP-only captures do not include DIFOP; vertical angles default to a uniform
-16°…+16° fan, horizontal channel offsets default to 0.
"""
from __future__ import annotations
from dataclasses import dataclass
import numpy as np
from capture_format_v2 import CaptureFile
PACKET_LENGTH = 1248
DATA_START = 42
BLOCKS = 12
BLOCK_LENGTH = 100
CHANNELS = 32
MIN_FRAME_POINTS_DEFAULT = 100
DOTNET_UNIX_EPOCH_TICKS = 621355968000000000
def ticks_to_unix_ns(ticks: int) -> int:
return (ticks - DOTNET_UNIX_EPOCH_TICKS) * 100
def default_vertical_deg() -> np.ndarray:
return -16.0 + np.arange(CHANNELS, dtype=np.float64) * (32.0 / (CHANNELS - 1))
def default_horizontal_deg() -> np.ndarray:
return np.zeros(CHANNELS, dtype=np.float64)
def read_u16_be(packet: bytes, index: int) -> int:
return (packet[index] << 8) | packet[index + 1]
def device_timestamp_ms(packet: bytes) -> int:
seconds = int.from_bytes(packet[20:26], "big")
microseconds = int.from_bytes(packet[26:30], "big")
return seconds * 1000 + microseconds // 1000
def distance_unit_mm(packet: bytes, *, auto: bool = True, fallback: float = 2.5) -> float:
if not auto:
return float(fallback)
return 2.5 if packet[17] == 1 else 0.5
def normalize_azimuth_deg(angle: float) -> float:
while angle > 180.0:
angle -= 360.0
while angle < -180.0:
angle += 360.0
return angle
@dataclass
class LidarFrameExport:
t_start_s: float
t_end_s: float
points_xyz: np.ndarray # (N, 3) metres
@dataclass
class LidarFramePolarExport:
"""One H32 frame in the calibration ``points_raw`` polar contract.
Columns: ``d_mm, azimuth_deg, altitude_deg, intensity, progression``.
Azimuth already includes the H32 channel horizontal offset and sign flip so
``rigorous_calibration.load_npz_xyz`` reproduces the same Cartesian points.
"""
t_start_s: float
t_end_s: float
points_raw: np.ndarray # (N, 5) float32
host_receive_utc_ns: int
def decode_packet_points(
packet: bytes,
vertical_deg: np.ndarray,
horizontal_deg: np.ndarray,
*,
min_range_m: float = 0.3,
max_range_m: float = 120.0,
) -> tuple[list[float], np.ndarray]:
"""Decode one MSOP packet into block azimuths and concatenated XYZ points."""
if len(packet) != PACKET_LENGTH:
return [], np.zeros((0, 3), dtype=np.float64)
unit = distance_unit_mm(packet)
az_list: list[float] = []
chunks: list[np.ndarray] = []
idx = DATA_START
for _block in range(BLOCKS):
if idx + BLOCK_LENGTH > PACKET_LENGTH or packet[idx] != 255 or packet[idx + 1] != 238:
break
az = read_u16_be(packet, idx + 2) * 0.01
az_list.append(az)
pts = _block_points(
packet,
idx,
az,
unit,
vertical_deg,
horizontal_deg,
min_range_m=min_range_m,
max_range_m=max_range_m,
)
if pts.shape[0]:
chunks.append(pts)
idx += BLOCK_LENGTH
if not chunks:
return az_list, np.zeros((0, 3), dtype=np.float64)
return az_list, np.vstack(chunks)
def _block_points(
packet: bytes,
block_offset: int,
az_deg: float,
unit_mm: float,
vertical_deg: np.ndarray,
horizontal_deg: np.ndarray,
*,
min_range_m: float,
max_range_m: float,
) -> np.ndarray:
xs: list[float] = []
ys: list[float] = []
zs: list[float] = []
idx = block_offset + 4 # after FF EE + azimuth
for ch in range(CHANNELS):
raw = read_u16_be(packet, idx)
idx += 3
if raw == 0:
continue
d_m = (raw * unit_mm) * 0.001
if d_m < min_range_m or d_m > max_range_m:
continue
az_ch = np.deg2rad(normalize_azimuth_deg(-(az_deg + float(horizontal_deg[ch]))))
alt = np.deg2rad(float(vertical_deg[ch]))
cos_alt = np.cos(alt)
xs.append(d_m * cos_alt * np.cos(az_ch))
ys.append(d_m * cos_alt * np.sin(az_ch))
zs.append(d_m * np.sin(alt))
if not xs:
return np.zeros((0, 3), dtype=np.float64)
return np.column_stack([xs, ys, zs]).astype(np.float64, copy=False)
def _block_points_raw(
packet: bytes,
block_offset: int,
az_deg: float,
unit_mm: float,
vertical_deg: np.ndarray,
horizontal_deg: np.ndarray,
*,
min_range_m: float,
max_range_m: float,
) -> np.ndarray:
"""Return polar ``points_raw`` rows compatible with ``load_npz_xyz``."""
rows: list[list[float]] = []
idx = block_offset + 4
for ch in range(CHANNELS):
raw = read_u16_be(packet, idx)
intensity = float(packet[idx + 2])
idx += 3
if raw == 0:
continue
d_mm = float(raw) * unit_mm
d_m = d_mm * 0.001
if d_m < min_range_m or d_m > max_range_m:
continue
az_ch = normalize_azimuth_deg(-(az_deg + float(horizontal_deg[ch])))
rows.append([d_mm, az_ch, float(vertical_deg[ch]), intensity, float(ch)])
if not rows:
return np.zeros((0, 5), dtype=np.float32)
return np.asarray(rows, dtype=np.float32)
def iter_h32_frames_polar(
capture: CaptureFile,
*,
min_frame_points: int = MIN_FRAME_POINTS_DEFAULT,
frame_stride: int = 1,
min_range_m: float = 0.3,
max_range_m: float = 120.0,
max_points_per_frame: int | None = None,
vertical_deg: np.ndarray | None = None,
horizontal_deg: np.ndarray | None = None,
) -> list[LidarFramePolarExport]:
"""Assemble MSOP packets into polar frames for the RTKLiDAR combined contract."""
vertical = default_vertical_deg() if vertical_deg is None else np.asarray(vertical_deg, dtype=np.float64)
horizontal = default_horizontal_deg() if horizontal_deg is None else np.asarray(horizontal_deg, dtype=np.float64)
if vertical.shape != (CHANNELS,) or horizontal.shape != (CHANNELS,):
raise ValueError(f"vertical/horizontal must have shape ({CHANNELS},)")
frames: list[LidarFramePolarExport] = []
point_chunks: list[np.ndarray] = []
t_start: float | None = None
t_end: float | None = None
host_ns = 0
prev_az: float | None = None
kept = 0
stride = max(1, int(frame_stride))
def emit() -> None:
nonlocal point_chunks, t_start, t_end, host_ns, kept
if not point_chunks or t_start is None or t_end is None:
point_chunks = []
t_start = t_end = None
return
points = np.vstack(point_chunks)
point_chunks = []
start_s, end_s = t_start, t_end
frame_host = host_ns
t_start = t_end = None
if points.shape[0] < min_frame_points:
return
if kept % stride != 0:
kept += 1
return
kept += 1
if max_points_per_frame is not None and points.shape[0] > max_points_per_frame:
select = np.linspace(0, points.shape[0] - 1, max_points_per_frame, dtype=int)
points = points[select]
if end_s <= start_s:
end_s = start_s + 0.1
frames.append(
LidarFramePolarExport(
t_start_s=start_s,
t_end_s=end_s,
points_raw=points.astype(np.float32, copy=False),
host_receive_utc_ns=int(frame_host),
)
)
for chunk in capture.chunks:
packet = chunk.raw
if len(packet) != PACKET_LENGTH:
continue
packet_t = device_timestamp_ms(packet) * 1e-3
unit = distance_unit_mm(packet)
chunk_host = ticks_to_unix_ns(chunk.receive_utc_ticks)
idx = DATA_START
for _block in range(BLOCKS):
if idx + BLOCK_LENGTH > PACKET_LENGTH or packet[idx] != 255 or packet[idx + 1] != 238:
break
az = read_u16_be(packet, idx + 2) * 0.01
if prev_az is not None and prev_az > 270.0 and az < 90.0:
emit()
prev_az = az
pts = _block_points_raw(
packet,
idx,
az,
unit,
vertical,
horizontal,
min_range_m=min_range_m,
max_range_m=max_range_m,
)
if pts.shape[0]:
if t_start is None:
t_start = packet_t
t_end = packet_t
host_ns = chunk_host
point_chunks.append(pts)
idx += BLOCK_LENGTH
emit()
return frames
def iter_h32_frames(
capture: CaptureFile,
*,
min_frame_points: int = MIN_FRAME_POINTS_DEFAULT,
frame_stride: int = 1,
min_range_m: float = 0.3,
max_range_m: float = 120.0,
max_points_per_frame: int | None = None,
vertical_deg: np.ndarray | None = None,
horizontal_deg: np.ndarray | None = None,
) -> list[LidarFrameExport]:
"""Assemble MSOP packets into frames using the 270°→90° azimuth wrap."""
vertical = default_vertical_deg() if vertical_deg is None else np.asarray(vertical_deg, dtype=np.float64)
horizontal = default_horizontal_deg() if horizontal_deg is None else np.asarray(horizontal_deg, dtype=np.float64)
if vertical.shape != (CHANNELS,) or horizontal.shape != (CHANNELS,):
raise ValueError(f"vertical/horizontal must have shape ({CHANNELS},)")
frames: list[LidarFrameExport] = []
point_chunks: list[np.ndarray] = []
t_start: float | None = None
t_end: float | None = None
prev_az: float | None = None
kept = 0
stride = max(1, int(frame_stride))
def emit() -> None:
nonlocal point_chunks, t_start, t_end, kept
if not point_chunks or t_start is None or t_end is None:
point_chunks = []
t_start = t_end = None
return
points = np.vstack(point_chunks)
point_chunks = []
start_s, end_s = t_start, t_end
t_start = t_end = None
if points.shape[0] < min_frame_points:
return
if kept % stride != 0:
kept += 1
return
kept += 1
if max_points_per_frame is not None and points.shape[0] > max_points_per_frame:
select = np.linspace(0, points.shape[0] - 1, max_points_per_frame, dtype=int)
points = points[select]
if end_s <= start_s:
end_s = start_s + 0.1
frames.append(LidarFrameExport(t_start_s=start_s, t_end_s=end_s, points_xyz=points))
for chunk in capture.chunks:
packet = chunk.raw
if len(packet) != PACKET_LENGTH:
continue
packet_t = device_timestamp_ms(packet) * 1e-3
unit = distance_unit_mm(packet)
idx = DATA_START
for _block in range(BLOCKS):
if idx + BLOCK_LENGTH > PACKET_LENGTH or packet[idx] != 255 or packet[idx + 1] != 238:
break
az = read_u16_be(packet, idx + 2) * 0.01
if prev_az is not None and prev_az > 270.0 and az < 90.0:
emit()
prev_az = az
pts = _block_points(
packet,
idx,
az,
unit,
vertical,
horizontal,
min_range_m=min_range_m,
max_range_m=max_range_m,
)
if pts.shape[0]:
if t_start is None:
t_start = packet_t
t_end = packet_t
point_chunks.append(pts)
idx += BLOCK_LENGTH
emit()
return frames
+113
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@@ -0,0 +1,113 @@
"""Decode Wheeltec N300 FDILink IMU frames from a V2 .rscap capture."""
from __future__ import annotations
import struct
from dataclasses import dataclass
import numpy as np
from capture_format_v2 import CaptureFile, RawChunk, iter_contiguous_segments
@dataclass(frozen=True)
class ImuSample:
t_s: float
gyro_rad_s: tuple[float, float, float]
accel_m_s2: tuple[float, float, float]
host_receive_utc_ticks: int
device_timestamp_us: int
def crc8_fdilink(data: bytes) -> int:
crc = 0
for value in data:
crc ^= value
for _ in range(8):
crc = ((crc << 1) ^ 0x07) & 0xFF if crc & 0x80 else (crc << 1) & 0xFF
return crc
def crc16_fdilink(data: bytes) -> int:
crc = 0
for value in data:
crc ^= value << 8
for _ in range(8):
crc = ((crc << 1) ^ 0x1021) & 0xFFFF if crc & 0x8000 else (crc << 1) & 0xFFFF
return crc
def _host_ticks_for_span(chunks: list[RawChunk], start: int, end: int) -> int:
stream_offset = 0
last = chunks[0]
for chunk in chunks:
next_offset = stream_offset + len(chunk.raw)
if start < next_offset and end > stream_offset:
last = chunk
stream_offset = next_offset
return last.receive_utc_ticks
def iter_n300_imu_samples(capture: CaptureFile) -> list[ImuSample]:
"""Return CRC-valid MSG_IMU (0x40) samples sorted by device timestamp."""
samples: list[ImuSample] = []
expected_lengths = {0x40: 56, 0x41: 48}
for _segment_id, chunks in iter_contiguous_segments(capture.chunks):
stream = b"".join(chunk.raw for chunk in chunks)
cursor = 0
while cursor < len(stream):
start = stream.find(b"\xFC", cursor)
if start < 0:
break
if start + 8 > len(stream):
break
payload_length = stream[start + 2]
end = start + payload_length + 8
if end > len(stream):
if stream.find(b"\xFC", start + 1) < 0:
break
cursor = start + 1
continue
frame = stream[start:end]
if frame[-1] != 0xFD:
cursor = start + 1
continue
packet_id = frame[1]
payload = frame[7:-1]
header_ok = crc8_fdilink(frame[:4]) == frame[4]
payload_ok = crc16_fdilink(payload) == int.from_bytes(frame[5:7], "big")
expected = expected_lengths.get(packet_id)
length_ok = expected is None or len(payload) == expected
if not (header_ok and payload_ok and length_ok):
cursor = start + 1
continue
if packet_id == 0x40:
gyro = struct.unpack_from("<3f", payload, 0)
accel = struct.unpack_from("<3f", payload, 12)
device_us = struct.unpack_from("<q", payload, 48)[0]
samples.append(
ImuSample(
t_s=float(device_us) * 1e-6,
gyro_rad_s=gyro,
accel_m_s2=accel,
host_receive_utc_ticks=_host_ticks_for_span(chunks, start, end),
device_timestamp_us=int(device_us),
)
)
cursor = end
samples.sort(key=lambda sample: (sample.t_s, sample.device_timestamp_us))
return samples
def samples_to_arrays(samples: list[ImuSample]) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
if not samples:
return (
np.zeros(0, dtype=np.float64),
np.zeros((0, 3), dtype=np.float64),
np.zeros((0, 3), dtype=np.float64),
)
t = np.asarray([sample.t_s for sample in samples], dtype=np.float64)
gyro = np.asarray([sample.gyro_rad_s for sample in samples], dtype=np.float64)
accel = np.asarray([sample.accel_m_s2 for sample in samples], dtype=np.float64)
return t, gyro, accel
+35
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@@ -131,6 +131,39 @@ def parse_heading(line: str) -> dict:
}
def parse_pvtslna(line: str) -> dict:
"""Parse Unicore/G90 ``#PVTSLNA`` into GGA-compatible position fields.
``fix_quality`` is synthesized as 4 when checksum-valid coordinates exist so
the existing prepare gate (accepted fixes {4,5}) keeps working. Position
stddevs are retained for audits.
"""
star = line.rfind("*")
fields = line[1:star if star >= 0 else None].split(",")
if len(fields) < 16:
raise ValueError("PVTSLNA has too few fields")
tow = safe_float(fields[5])
return {
"type": "PVTSLNA",
"gnss_week": safe_int(fields[4]),
"gnss_tow_ms": int(tow) if tow is not None else None,
"altitude_m": safe_float(fields[10]),
"lat_deg": safe_float(fields[11]),
"lon_deg": safe_float(fields[12]),
"height_std_m": safe_float(fields[13]),
"latitude_std_m": safe_float(fields[14]),
"longitude_std_m": safe_float(fields[15]),
# Downstream prepare still filters on NMEA-style fix quality.
"fix_quality": 4,
"satellites": -1,
"hdop": None,
"differential_age_s": None,
"position_time_utc": "",
"geoid_separation_m": None,
"station_id": "",
}
def chunk_source(chunks: list[RawChunk], offset: int, end: int) -> dict:
first = chunks[0]
last = chunks[-1]
@@ -184,6 +217,8 @@ def parse_rtk_capture(capture: CaptureFile) -> list[dict]:
try:
if line.startswith("$GNGGA") or line.startswith("$GPGGA"):
row.update(parse_gga(line))
elif line.startswith("#PVTSLNA"):
row.update(parse_pvtslna(line))
elif line.startswith("#UNIHEADINGA"):
row.update(parse_heading(line))
except ValueError as ex:
+110 -1
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@@ -1,6 +1,7 @@
from __future__ import annotations
import bisect
import struct
from pipeline_common import *
from capture_format_v2 import CaptureFile, RawChunk, iter_contiguous_segments
@@ -39,6 +40,7 @@ def source_for_span(chunks: list[RawChunk], start: int, end: int, segment_id: in
"host_receive_monotonic_ticks": end_chunk.receive_monotonic_ticks,
}
def parse_rtk_capture(capture: CaptureFile) -> list[dict]:
rows = []
for segment_id, chunks in iter_contiguous_segments(capture.chunks):
@@ -60,6 +62,8 @@ def parse_rtk_capture(capture: CaptureFile) -> list[dict]:
try:
if line.startswith("$GNGGA") or line.startswith("$GPGGA"):
row.update(parse_gga(line))
elif line.startswith("#PVTSLNA"):
row.update(parse_pvtslna(line))
elif line.startswith("#UNIHEADINGA"):
row.update(parse_heading(line))
except ValueError as ex:
@@ -68,7 +72,103 @@ def parse_rtk_capture(capture: CaptureFile) -> list[dict]:
return rows
def parse_imu_capture(capture: CaptureFile) -> list[dict]:
def crc8_fdilink(data: bytes) -> int:
crc = 0
for value in data:
crc ^= value
for _ in range(8):
crc = ((crc << 1) ^ 0x07) & 0xFF if crc & 0x80 else (crc << 1) & 0xFF
return crc
def crc16_fdilink(data: bytes) -> int:
crc = 0
for value in data:
crc ^= value << 8
for _ in range(8):
crc = ((crc << 1) ^ 0x1021) & 0xFFFF if crc & 0x8000 else (crc << 1) & 0xFFFF
return crc
def parse_n300_imu_capture(capture: CaptureFile) -> list[dict]:
"""Parse Wheeltec N300 FDILink IMU frames; normalize to HI13-like keys."""
rows = []
expected_lengths = {0x40: 56, 0x41: 48}
for segment_id, chunks in iter_contiguous_segments(capture.chunks):
stream = b"".join(chunk.raw for chunk in chunks)
cursor = 0
while cursor < len(stream):
start = stream.find(b"\xFC", cursor)
if start < 0:
break
if start + 8 > len(stream):
break
payload_length = stream[start + 2]
end = start + payload_length + 8
if end > len(stream):
if stream.find(b"\xFC", start + 1) < 0:
break
cursor = start + 1
continue
frame = stream[start:end]
if frame[-1] != 0xFD:
cursor = start + 1
continue
packet_id = frame[1]
payload = frame[7:-1]
header_ok = crc8_fdilink(frame[:4]) == frame[4]
payload_ok = crc16_fdilink(payload) == int.from_bytes(frame[5:7], "big")
expected = expected_lengths.get(packet_id)
length_ok = expected is None or len(payload) == expected
row = {
"type": "N300",
"tag": int(packet_id),
"frame_length": len(frame),
"crc_valid": bool(header_ok and payload_ok and length_ok),
"raw_frame_hex": frame.hex(),
}
row.update(source_for_span(chunks, start, end, segment_id))
if row["crc_valid"] and packet_id == 0x40:
try:
gyro = struct.unpack_from("<3f", payload, 0)
accel = struct.unpack_from("<3f", payload, 12)
device_us = struct.unpack_from("<q", payload, 48)[0]
row.update(
{
"device_timestamp_us": int(device_us),
# build_multisensor_npz.estimate_imu_times uses ms.
"device_timestamp_ms": int(device_us) // 1000,
"gyro_x_radps": gyro[0],
"gyro_y_radps": gyro[1],
"gyro_z_radps": gyro[2],
"accel_x_mps2": accel[0],
"accel_y_mps2": accel[1],
"accel_z_mps2": accel[2],
"pps_sync_stamp_ms": -1,
}
)
except (IndexError, struct.error, ValueError) as ex:
row["parse_error"] = str(ex)
row["crc_valid"] = False
elif row["crc_valid"] and packet_id == 0x41:
try:
device_us = struct.unpack_from("<q", payload, 40)[0]
row.update(
{
"device_timestamp_us": int(device_us),
"device_timestamp_ms": int(device_us) // 1000,
"pps_sync_stamp_ms": -1,
}
)
except (IndexError, struct.error, ValueError) as ex:
row["parse_error"] = str(ex)
rows.append(row)
cursor = end if row["crc_valid"] else start + 1
return rows
def parse_hi13_imu_capture(capture: CaptureFile) -> list[dict]:
rows = []
for segment_id, chunks in iter_contiguous_segments(capture.chunks):
stream = b"".join(chunk.raw for chunk in chunks)
@@ -104,3 +204,12 @@ def parse_imu_capture(capture: CaptureFile) -> list[dict]:
rows.append(row)
cursor = end
return rows
def parse_imu_capture(capture: CaptureFile) -> list[dict]:
"""Prefer N300 FDILink when present; fall back to legacy HI13."""
n300 = parse_n300_imu_capture(capture)
if any(row.get("crc_valid") and row.get("type") == "N300" for row in n300):
return n300
return parse_hi13_imu_capture(capture)