oscillation – We Mean You No Harm https://wemeanyounoharm.com Sun, 29 Mar 2026 12:11:24 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.4 230952698 Oscillation Ghojualamanchu https://wemeanyounoharm.com/oscillation/ Sun, 29 Mar 2026 12:11:24 +0000 https://wemeanyounoharm.com/?p=41
Oscillation — Ghojualamanchu MIDI Robotics Bridge

OSCILLATION

Ghojualamanchu → MIDI → Harmonic Robotics

A cognitive agent that thinks in oscillations, bridged to physical actuators via MIDI.

What Is Oscillation?

Oscillation is a project to build a closed-loop bridge between a cognitive agent (Ghojualamanchu) and physical actuators (servos, motors, drones), using MIDI as the transmission protocol and harmonic oscillation as the unified control language.

The core bet: Ghojualamanchu thinks in oscillations. MIDI carries oscillations. Harmonic oscillation — ω, amplitude, phase, damping — is the same math whether describing a brain wave, a musical note, or a robot’s gait.

Architecture

Ghojualamanchu (cognition)
↓ writes oscillation_target.json
↓ mido / USB MIDI
USB MIDI → ESP32-S3 (hopf_cpg_firmware.ino)
CC1=ω CC2=A CC3=φ CC4=ζ | Note#=servo | PitchBend=fine ω
↓ Hopf CPG @ 500 Hz → SimpleFOC → PWM
SG90 Servo ↔ MPU6050 / AS5600
↓ serial / OSC telemetry
resonance_monitor.py (FFT → ω_measured)
↓ writes resonance_report.json
← Ghojualamanchu (observe / correct)

Oscillation Parameters

SymbolNameMIDI EquivalentRange
ωAngular frequencyCC74 (log-mapped)0.1–25 rad/s
AAmplitudeNote velocity0.0–1.0
φPhase offsetCC3 / pitch bend0–2π rad
ζDamping ratioCC40.0–1.0

Two-Speed Loop

LoopRateRuns OnWhat It Does
Slow (cognitive)~1 HzGhojualamanchuReads resonance_report.json, updates oscillation_target.json, logs to hippocampus
Fast (motor)500 HzESP32 firmwareHopf CPG integration, SimpleFOC closed-loop, encoder/IMU feedback

Build Stages

StageGoalCostStatus
ooze Ghojualamanchu → MIDI → one servo moves ~€25 Next
pwm_test Encoder feedback → FFT → ω_measured within 5% +€8 Todo
midi_hopfcpg Hopf CPG firmware running on ESP32, driven by MIDI CC Software Todo
telemetry MPU6050 → ESP32 → OSC → Ghojualamanchu observes Software Todo
full_loop Ghojualamanchu closes the loop Software Todo
multi_joint 4 servos, MIDI clock sync, correct phase offsets +€25 Todo
swarm N drones, Kuramoto coupling, order parameter r Varies Todo

MIDI CC Protocol

ChannelUse
Ch 1Servos 1–8: CC1=ω, CC2=A, CC3=φ, CC4=ζ per servo
Ch 4System: CC64=EMERGENCY_STOP, CC65=RESET, CC66=MODE, CC67=CLOCK_PHASE_MASTER
Frequency mapping: ω = 0.1 × 2^(CC/16) rad/s
CC=0 → 0.1 rad/s  |  CC=64 → 1.6 rad/s  |  CC=96 → 6.4 rad/s  |  CC=127 → 25.6 rad/s

Key Files

FLUX Codec Integration

FLUX (physics-based video compression at /home/workspace/flux-codec/) provides motion fields as the oscillation parameter source:

Video / Physics Sim
↓ FLUX Block 3 (optical flow)
↓ flux_to_omega.py (FFT → ω, A, φ, γ)
↓ oscillation_target.json
→ Ghojualamanchu → MIDI CC → Servo
Note on Exanima: Exanima was originally referenced as a physics training source. It is a medieval combat ARPG — not a robotics simulator, no API, no motion capture export. Use MuJoCo or Genesis for sim-to-real training instead.

Research Key Findings

  1. MIDI → servo is proven — MidiBanger, Adafruit Robot Lyre, jammotors all confirm this works
  2. The novel contribution is closed-loop feedback: sensor → Ghojualamanchu → parameter correction → MIDI → CPG
  3. CPG on microcontroller is standard — MIDI is configuration, not streaming; firmware interpolates at 1–10 kHz
  4. Kuramoto model for swarm sync: Ghojualamanchu broadcasts MIDI clock, computes order parameter r, adjusts tempo
  5. MPU6050 + ESP32 = €4–8 sensor stack for full oscillator state (position, velocity, acceleration)

Budget

StageCost
ooze (first servo)~€25
Full project (4 servos)~€60–80

Next Actions

  1. Buy hardware: ESP32-S3-DevKitC-1 + SG90 + AS5600 + MPU6050 (~€20–25)
  2. Flash hopf_cpg_firmware.ino to ESP32-S3, verify serial MIDI parsing
  3. Install mido + rtmidi on Zo Computer, test MIDI out to ESP32
  4. Wire SG90 to ESP32, verify servo responds to MIDI CC
  5. Connect AS5600 via I2C, verify encoder reads via serial
  6. Run resonance_monitor.py, verify FFT ω_measured accuracy
  7. Integrate into Ghojualamanchu — read resonance_report.json on heartbeat

Oscillation SOP v1.0 — built from 18 research cycles
Ghojualamanchu × MIDI × Harmonic Robotics

Project_OscillationDownload
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