eSlider
3deaa382e1
One process per drone: seeded patrol kinematics, sensor streams at realistic rates, detection events, hot current/ blocks sealed into Hive-partitioned Parquet, and the compact UDP state broadcast with peer RSSI derivation. Scales via docker compose --scale.
81 lines
2.4 KiB
Python
81 lines
2.4 KiB
Python
"""Sensor row generators. Pure functions: (pose, rng, ts) -> row dict.
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Every row carries int64 epoch nanoseconds. Values are emitted at full float
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precision - quantization happens only in the broadcast payload, never in
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stored telemetry.
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"""
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from __future__ import annotations
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import math
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import random
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from typing import Any
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from .flight import Pose
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Row = dict[str, Any]
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def imu_row(pose: Pose, rng: random.Random, ts_ns: int) -> Row:
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return {
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"ts_ns": ts_ns,
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"accel_x": rng.gauss(0.0, 0.35),
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"accel_y": rng.gauss(0.0, 0.35),
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"accel_z": rng.gauss(-9.81, 0.25),
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"gyro_x": math.radians(rng.gauss(pose.roll, 0.8)),
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"gyro_y": math.radians(rng.gauss(pose.pitch, 0.8)),
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"gyro_z": math.radians(rng.gauss(0.0, 0.5)),
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}
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def baro_row(pose: Pose, rng: random.Random, ts_ns: int) -> Row:
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pressure = 101325.0 * math.exp(-pose.z / 8434.0) + rng.gauss(0.0, 4.0)
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return {"ts_ns": ts_ns, "pressure_pa": pressure, "alt_est_m": pose.z + rng.gauss(0.0, 0.3)}
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def temp_row(_pose: Pose, rng: random.Random, ts_ns: int) -> Row:
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return {
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"ts_ns": ts_ns,
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"cpu_c": 55.0 + rng.gauss(0.0, 3.0),
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"gpu_c": 62.0 + rng.gauss(0.0, 4.0),
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"ambient_c": 24.0 + rng.gauss(0.0, 0.5),
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}
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def battery_row(_pose: Pose, rng: random.Random, ts_ns: int, elapsed_s: float, duration_s: float) -> Row:
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level = max(0.0, 100.0 - 80.0 * elapsed_s / max(duration_s, 1.0) + rng.gauss(0.0, 0.2))
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return {"ts_ns": ts_ns, "level_pct": level, "voltage_v": 22.2 * (0.85 + 0.15 * level / 100.0)}
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DETECTION_CLASSES = ("vehicle", "person", "animal", "structure", "unknown")
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def detection_row(pose: Pose, rng: random.Random, ts_ns: int) -> Row:
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return {
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"ts_ns": ts_ns,
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"cls": rng.choice(DETECTION_CLASSES),
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"confidence": round(rng.uniform(0.42, 0.99), 3),
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"obj_x": pose.x + rng.uniform(-40.0, 40.0),
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"obj_y": pose.y + rng.uniform(-40.0, 40.0),
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"obj_z": rng.uniform(0.0, 5.0),
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"ego_x": pose.x,
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"ego_y": pose.y,
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"ego_z": pose.z,
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}
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def state_row(pose: Pose, ts_ns: int) -> Row:
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return {
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"ts_ns": ts_ns,
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"pos_x": pose.x,
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"pos_y": pose.y,
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"pos_z": pose.z,
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"roll": pose.roll,
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"pitch": pose.pitch,
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"yaw": pose.yaw,
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"vel_x": pose.vx,
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"vel_y": pose.vy,
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"vel_z": pose.vz,
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"frame_ref": 0,
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}
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