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Add verification script for IMU gravity compensation and velocity integration

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Brunsmeier
2026-07-02 11:19:53 +08:00
parent e0f777837b
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README.md
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@ -11,6 +11,7 @@ This project bridges IMU data through an ESP32 to a PC, with optional gripper/re
- `c`: CLOSE
- `s`: STOP
- Generates statistics, CSV files, and plots from either live serial data or saved text logs.
- Estimates world-frame linear acceleration and velocity from IMU acceleration and Euler angles.
- Uses a physical switch on GPIO27 to trigger one-shot gripper open/close pulses.
## Files
@ -20,7 +21,7 @@ This project bridges IMU data through an ESP32 to a PC, with optional gripper/re
| `main.py` | Main MicroPython program for the ESP32. It reads the IMU, controls DIO, and streams USB serial packets. |
| `esp_bridge.py` | PC-side Python wrapper class for integrating the ESP32 bridge into other programs. |
| `pc_reader.py` | PC-side real-time serial reader with keyboard gripper commands. |
| `visualise.py` | Sampling, statistics, CSV export, and plotting tool. |
| `visualise.py` | Sampling, statistics, CSV export, plotting, linear-acceleration estimation, and velocity integration tool. |
| `test.py` | ESP32 UART pin scan/debug helper. |
| `imu_data.csv` | Example or exported IMU sample data. |
| `rcd.txt` | Example text log from `pc_reader.py`. |
@ -172,12 +173,62 @@ Read from a `pc_reader.py` text log and plot it:
python3 visualise.py --file rcd.txt --output imu_quality.png
```
If the output file already exists, `visualise.py` appends a timestamp to avoid overwriting it, for example:
`visualise.py` now adds derived motion columns before saving or plotting:
| Column | Description |
| --- | --- |
| `lin_acc_x_ms2`, `lin_acc_y_ms2`, `lin_acc_z_ms2` | Estimated world-frame linear acceleration in `m/s^2` after gravity and bias compensation. |
| `vel_x_ms`, `vel_y_ms`, `vel_z_ms` | Estimated world-frame velocity in `m/s` from integrating linear acceleration. |
The generated plot contains six stacked views:
- raw acceleration
- linear acceleration
- velocity
- gyro
- angle
- packet frequency
CSV files are saved under `csv/`, PNG files are saved under `png/`, and other output extensions are saved under `output/`. If the target file already exists, `visualise.py` appends a timestamp to avoid overwriting it, for example:
```text
imu_quality_20260701_131902.png
png/imu_quality_20260701_131902.png
```
## Linear Acceleration And Velocity
The raw accelerometer output includes both motion acceleration and the support-force/gravity-related acceleration measured by the IMU. When the sensor is placed horizontally and kept still, it will still measure about `1g` on the vertical axis. This is expected: the table support force prevents free fall, and the accelerometer senses that proper acceleration.
Because of this, `visualise.py` removes the static `1g` component before integrating velocity. The current calculation is:
1. Read raw acceleration in the IMU/body frame: `acc_x_g`, `acc_y_g`, `acc_z_g`.
2. Convert Euler angles to a body-to-world rotation matrix:
```python
R = Rz(yaw) @ Ry(pitch) @ Rx(roll)
```
3. Rotate body-frame acceleration into the world frame:
```python
acc_world_g = R @ acc_body_g
```
4. Subtract the world Z-axis support-force/gravity component:
```python
linear_acc_world_g = acc_world_g - [0, 0, gravity_sign]
```
The default call uses `gravity_sign=1.0`, so a horizontally placed, still sensor is expected to have approximately `+1g` on the world Z axis before compensation.
5. Convert from `g` to `m/s^2` with `9.81`.
6. Estimate a small acceleration bias from the first `bias_seconds` seconds, default `1.0` second, and subtract it.
7. Apply an acceleration deadband, default `0.15 m/s^2`, to reduce small stationary noise.
8. Integrate acceleration to velocity with a small decay factor, default `vel_decay=0.995`, to limit drift.
This velocity estimate is useful for short-duration motion checks and relative comparisons. It will drift over time because low-cost IMU acceleration, attitude error, and numerical integration all accumulate error. Keep the sensor still for the first second when possible so the initial bias estimate is meaningful.
## Packet Protocol
The ESP32-to-PC binary packet format is defined in `main.py`, `pc_reader.py`, and `esp_bridge.py`:

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@ -0,0 +1,570 @@
import argparse
import ast
import csv
import math
import os
import re
import sys
import time
from datetime import datetime
os.environ.setdefault("MPLCONFIGDIR", "/tmp/matplotlib")
import matplotlib.pyplot as plt
import numpy as np
import serial
from pc_reader import PACKET_SIZE, SYNC, decode_packet
TEXT_LINE_RE = re.compile(
r"#?\s*(?P<count>\d+)\s+"
r"(?P<freq>[-+]?\d+(?:\.\d+)?)Hz\s+"
r"DIN=(?P<din>\[[^\]]+\])\s+"
r"DOUT=(?P<dout>\[[^\]]+\])\s+"
r"ACC=(?P<acc>\[[^\]]+\])\s+"
r"GYRO=(?P<gyro>\[[^\]]+\])\s+"
r"ANGLE=(?P<angle>\[[^\]]+\])"
)
def flatten_packet(data, t_s, freq_hz):
return {
"t_s": t_s,
"acc_x_g": data["acc_g"][0],
"acc_y_g": data["acc_g"][1],
"acc_z_g": data["acc_g"][2],
"gyro_x_dps": data["gyro_dps"][0],
"gyro_y_dps": data["gyro_dps"][1],
"gyro_z_dps": data["gyro_dps"][2],
"angle_x_deg": data["angle_deg"][0],
"angle_y_deg": data["angle_deg"][1],
"angle_z_deg": data["angle_deg"][2],
"temp_c": data["temp_c"],
"freq_hz": freq_hz,
"din0": data["din"][0],
"din1": data["din"][1],
"din2": data["din"][2],
"din3": data["din"][3],
"dout0": data["dout"][0],
"dout1": data["dout"][1],
}
def read_serial_samples(port, baud, seconds=None, max_samples=None, max_gap_ms=1000):
samples = []
buffer = bytearray()
last_t_ms = None
elapsed_s = 0.0
bad_delta_count = 0
start = time.monotonic()
with serial.Serial(port, baud, timeout=1) as ser:
print(f"Reading {port} at {baud} baud...", file=sys.stderr)
while True:
if seconds is not None and time.monotonic() - start >= seconds:
break
if max_samples is not None and len(samples) >= max_samples:
break
chunk = ser.read(ser.in_waiting or 1)
if chunk:
buffer.extend(chunk)
while len(buffer) >= PACKET_SIZE:
sync_index = buffer.find(SYNC)
if sync_index < 0:
del buffer[:-1]
break
if sync_index:
del buffer[:sync_index]
if len(buffer) < PACKET_SIZE:
break
packet = bytes(buffer[:PACKET_SIZE])
if (sum(packet[:-1]) & 0xFF) != packet[-1]:
del buffer[0]
continue
del buffer[:PACKET_SIZE]
data = decode_packet(packet)
if last_t_ms is None:
freq_hz = 0.0
else:
delta = (data["t_ms"] - last_t_ms) & 0xFFFFFFFF
if 0 < delta <= max_gap_ms:
elapsed_s += delta / 1000.0
freq_hz = 1000.0 / delta
else:
bad_delta_count += 1
freq_hz = 0.0
last_t_ms = data["t_ms"]
samples.append(flatten_packet(data, elapsed_s, freq_hz))
if max_samples is not None and len(samples) >= max_samples:
break
if bad_delta_count:
print(f"Ignored {bad_delta_count} abnormal packet time delta(s).", file=sys.stderr)
return samples
def read_text_log(path):
samples = []
t_s = 0.0
with open(path, "r", encoding="utf-8") as f:
for line in f:
match = TEXT_LINE_RE.search(line)
if not match:
continue
freq_hz = float(match.group("freq"))
din = ast.literal_eval(match.group("din"))
dout = ast.literal_eval(match.group("dout"))
acc = ast.literal_eval(match.group("acc"))
gyro = ast.literal_eval(match.group("gyro"))
angle = ast.literal_eval(match.group("angle"))
if samples and freq_hz > 0:
t_s += 1.0 / freq_hz
samples.append(
{
"t_s": t_s,
"acc_x_g": acc[0],
"acc_y_g": acc[1],
"acc_z_g": acc[2],
"gyro_x_dps": gyro[0],
"gyro_y_dps": gyro[1],
"gyro_z_dps": gyro[2],
"angle_x_deg": angle[0],
"angle_y_deg": angle[1],
"angle_z_deg": angle[2],
"temp_c": np.nan,
"freq_hz": freq_hz,
"din0": din[0],
"din1": din[1],
"din2": din[2],
"din3": din[3],
"dout0": dout[0],
"dout1": dout[1],
}
)
return samples
def verify_gravity_body_g(roll_deg, pitch_deg, gravity_sign=1.0):
"""
Provider's roll/pitch gravity projection.
Assumption:
roll = angle_x_deg
pitch = angle_y_deg
yaw is ignored.
gravity_sign:
+1.0 means horizontal static gravity is approximately +Z.
-1.0 means horizontal static gravity is approximately -Z.
"""
roll = math.radians(roll_deg)
pitch = math.radians(pitch_deg)
g_x = -math.sin(pitch)
g_y = math.cos(pitch) * math.sin(roll)
g_z = math.cos(pitch) * math.cos(roll)
return np.array([g_x, g_y, g_z], dtype=float) * gravity_sign
def add_verification(
samples,
gravity_sign=1.0,
bias_seconds=1.0,
acc_deadband=0.10,
vel_decay=0.995,
):
"""
Add Provider-method gravity compensation and simple velocity integration.
Output columns:
Provider_gx_g / Provider_gy_g / Provider_gz_g
Provider_lin_acc_x_g / y / z
Provider_lin_acc_x_ms2 / y / z
Provider_vel_x_ms / y / z
Provider_lin_acc_norm_ms2
Provider_vel_norm_ms
"""
if not samples:
return samples
raw_lin_acc_ms2 = []
for sample in samples:
acc_body_g = np.array(
[
sample["acc_x_g"],
sample["acc_y_g"],
sample["acc_z_g"],
],
dtype=float,
)
gravity_body_g = verify_gravity_body_g(
sample["angle_x_deg"],
sample["angle_y_deg"],
gravity_sign=gravity_sign,
)
linear_acc_body_g = acc_body_g - gravity_body_g
linear_acc_body_ms2 = linear_acc_body_g * 9.81
sample["Provider_gx_g"] = gravity_body_g[0]
sample["Provider_gy_g"] = gravity_body_g[1]
sample["Provider_gz_g"] = gravity_body_g[2]
sample["Provider_lin_acc_x_g_raw"] = linear_acc_body_g[0]
sample["Provider_lin_acc_y_g_raw"] = linear_acc_body_g[1]
sample["Provider_lin_acc_z_g_raw"] = linear_acc_body_g[2]
raw_lin_acc_ms2.append(linear_acc_body_ms2)
raw_lin_acc_ms2 = np.array(raw_lin_acc_ms2, dtype=float)
t0 = samples[0]["t_s"]
bias_indices = [
i
for i, sample in enumerate(samples)
if sample["t_s"] - t0 <= bias_seconds
]
if bias_indices:
acc_bias = np.mean(raw_lin_acc_ms2[bias_indices], axis=0)
else:
acc_bias = np.zeros(3, dtype=float)
print("Provider method")
print(f" gravity_sign: {gravity_sign}")
print(f" bias_seconds: {bias_seconds}")
print(f" estimated acc bias m/s^2: {acc_bias}")
v = np.zeros(3, dtype=float)
last_t = samples[0]["t_s"]
for i, sample in enumerate(samples):
t = sample["t_s"]
dt = t - last_t
last_t = t
if dt <= 0 or dt > 0.2:
dt = 0.0
linear_acc = raw_lin_acc_ms2[i] - acc_bias
if np.linalg.norm(linear_acc) < acc_deadband:
linear_acc[:] = 0.0
v = v * vel_decay + linear_acc * dt
sample["Provider_lin_acc_x_ms2"] = linear_acc[0]
sample["Provider_lin_acc_y_ms2"] = linear_acc[1]
sample["Provider_lin_acc_z_ms2"] = linear_acc[2]
sample["Provider_lin_acc_norm_ms2"] = float(np.linalg.norm(linear_acc))
sample["Provider_vel_x_ms"] = v[0]
sample["Provider_vel_y_ms"] = v[1]
sample["Provider_vel_z_ms"] = v[2]
sample["Provider_vel_norm_ms"] = float(np.linalg.norm(v))
return samples
def unique_path(path):
if not path:
return path
root, ext = os.path.splitext(os.path.basename(path))
ext = ext.lower()
if ext == ".csv":
folder = "csv"
elif ext == ".png":
folder = "png"
else:
folder = "output"
os.makedirs(folder, exist_ok=True)
new_path = os.path.join(folder, root + ext)
if not os.path.exists(new_path):
return new_path
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
return os.path.join(folder, f"{root}_{timestamp}{ext}")
def write_csv(samples, path):
if not samples:
return
columns = list(samples[0].keys())
with open(path, "w", newline="", encoding="utf-8") as f:
writer = csv.DictWriter(f, fieldnames=columns)
writer.writeheader()
writer.writerows(samples)
def print_stats(samples):
if not samples:
print("No samples parsed.")
return
print(f"Samples: {len(samples)}")
print(f"Duration: {samples[-1]['t_s'] - samples[0]['t_s']:.3f}s")
groups = (
("RAW ACC g", ("acc_x_g", "acc_y_g", "acc_z_g")),
("GYRO dps", ("gyro_x_dps", "gyro_y_dps", "gyro_z_dps")),
("ANGLE deg", ("angle_x_deg", "angle_y_deg", "angle_z_deg")),
(
"Provider GRAVITY g",
("Provider_gx_g", "Provider_gy_g", "Provider_gz_g"),
),
(
"Provider LINEAR ACC m/s^2",
(
"Provider_lin_acc_x_ms2",
"Provider_lin_acc_y_ms2",
"Provider_lin_acc_z_ms2",
"Provider_lin_acc_norm_ms2",
),
),
(
"Provider VELOCITY m/s",
(
"Provider_vel_x_ms",
"Provider_vel_y_ms",
"Provider_vel_z_ms",
"Provider_vel_norm_ms",
),
),
)
for group_name, fields in groups:
print(f"\n{group_name}")
for field in fields:
values = np.array([sample[field] for sample in samples], dtype=float)
diffs = np.diff(values)
diff_std = float(np.std(diffs)) if len(diffs) else 0.0
print(
" {:24s} mean={: .6f} std={:.6f} ptp={:.6f} final={: .6f} diff_std={:.6f}".format(
field,
float(np.mean(values)),
float(np.std(values)),
float(np.ptp(values)),
float(values[-1]),
diff_std,
)
)
freq = np.array([sample["freq_hz"] for sample in samples[1:]], dtype=float)
if len(freq):
print(
"\nFrequency Hz mean={:.3f} std={:.3f} min={:.3f} max={:.3f}".format(
float(np.mean(freq)),
float(np.std(freq)),
float(np.min(freq)),
float(np.max(freq)),
)
)
def plot_group(axis, t, samples, fields, ylabel):
for field in fields:
values = np.array([sample[field] for sample in samples], dtype=float)
axis.plot(t, values, label=field, linewidth=1.0)
axis.set_ylabel(ylabel)
axis.grid(True, alpha=0.3)
axis.legend(loc="upper right", ncol=3)
def plot_samples(samples, output=None, show=True):
if not samples:
raise ValueError("No samples to plot.")
t = np.array([sample["t_s"] for sample in samples], dtype=float)
fig, axes = plt.subplots(7, 1, sharex=True, figsize=(13, 15))
plot_group(
axes[0],
t,
samples,
("acc_x_g", "acc_y_g", "acc_z_g"),
"Raw acc (g)",
)
plot_group(
axes[1],
t,
samples,
("Provider_gx_g", "Provider_gy_g", "Provider_gz_g"),
"Estimated gravity (g)",
)
plot_group(
axes[2],
t,
samples,
(
"Provider_lin_acc_x_ms2",
"Provider_lin_acc_y_ms2",
"Provider_lin_acc_z_ms2",
),
"Provider linear acc (m/s²)",
)
plot_group(
axes[3],
t,
samples,
("Provider_lin_acc_norm_ms2",),
"Linear acc norm (m/s²)",
)
plot_group(
axes[4],
t,
samples,
("Provider_vel_x_ms", "Provider_vel_y_ms", "Provider_vel_z_ms"),
"Provider velocity (m/s)",
)
plot_group(
axes[5],
t,
samples,
("gyro_x_dps", "gyro_y_dps", "gyro_z_dps"),
"Gyro (deg/s)",
)
plot_group(
axes[6],
t,
samples,
("angle_x_deg", "angle_y_deg", "angle_z_deg"),
"Angle (deg)",
)
axes[6].set_xlabel("Time (s)")
fig.suptitle("Provider Method IMU Verification")
fig.tight_layout()
if output:
fig.savefig(output, dpi=160)
print(f"Saved plot to {output}")
if show:
plt.show()
def main():
parser = argparse.ArgumentParser(
description="Verify Provider roll/pitch gravity compensation method."
)
source = parser.add_mutually_exclusive_group(required=True)
source.add_argument("--file", help="pc_reader text log, for example rcd.txt")
source.add_argument("--port", help="ESP32 serial port, for example /dev/ttyUSB0")
parser.add_argument("--baud", type=int, default=115200)
parser.add_argument("--seconds", type=float, default=10.0)
parser.add_argument("--samples", type=int)
parser.add_argument("--max-gap-ms", type=int, default=1000)
parser.add_argument(
"--gravity-sign",
type=float,
default=1.0,
choices=[1.0, -1.0],
help="Use +1 if horizontal static acc_z is about +1g; use -1 if about -1g.",
)
parser.add_argument(
"--bias-seconds",
type=float,
default=1.0,
help="Use the first N seconds to estimate residual linear acceleration bias.",
)
parser.add_argument(
"--acc-deadband",
type=float,
default=0.10,
help="Set linear acceleration to zero if norm is below this value, unit m/s^2.",
)
parser.add_argument(
"--vel-decay",
type=float,
default=0.995,
help="Velocity decay factor to reduce long-term integration drift.",
)
parser.add_argument("--output", default="verify_l.png")
parser.add_argument("--csv", default="verify_l.csv")
parser.add_argument("--no-show", action="store_true")
args = parser.parse_args()
if args.file:
samples = read_text_log(args.file)
else:
samples = read_serial_samples(
args.port,
args.baud,
args.seconds,
args.samples,
args.max_gap_ms,
)
if not samples:
print("No samples parsed. Check input mode, serial port, baudrate, or log format.")
return
samples = add_verification(
samples,
gravity_sign=args.gravity_sign,
bias_seconds=args.bias_seconds,
acc_deadband=args.acc_deadband,
vel_decay=args.vel_decay,
)
print_stats(samples)
csv_path = unique_path(args.csv)
write_csv(samples, csv_path)
print(f"Saved CSV to {csv_path}")
output_path = unique_path(args.output)
plot_samples(samples, output=output_path, show=not args.no_show)
if __name__ == "__main__":
main()
# python3 verify.py --port /dev/ttyUSB0 --baud 115200 --seconds 10 --no-show