Metadata-Version: 2.4
Name: aether-robotics
Version: 3.5.0
Summary: Autonomous multi-agent robotics system with DRL-First Hybrid FDIR
Author: Chahel Paatur
License: MIT
Project-URL: Homepage, https://github.com/ChahelPaatur/AETHER
Project-URL: Repository, https://github.com/ChahelPaatur/AETHER
Project-URL: Issues, https://github.com/ChahelPaatur/AETHER/issues
Keywords: robotics,autonomous,FDIR,fault-detection,raspberry-pi,drone,AI
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: System :: Hardware
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.24.0
Requires-Dist: psutil>=5.9.0
Requires-Dist: requests>=2.32.0
Provides-Extra: full
Requires-Dist: anthropic>=0.50.0; extra == "full"
Requires-Dist: flask>=3.0.0; extra == "full"
Requires-Dist: opencv-python-headless>=4.8.0; extra == "full"
Requires-Dist: matplotlib>=3.7.0; extra == "full"
Provides-Extra: pi
Requires-Dist: picamera2; extra == "pi"
Requires-Dist: RPi.GPIO; extra == "pi"
Requires-Dist: gpiozero; extra == "pi"
Requires-Dist: smbus2; extra == "pi"
Provides-Extra: drone
Requires-Dist: pymavlink; extra == "drone"
Requires-Dist: pyserial; extra == "drone"
Provides-Extra: ml
Requires-Dist: ultralytics; extra == "ml"
Requires-Dist: scipy; extra == "ml"
Requires-Dist: scikit-learn; extra == "ml"
Dynamic: license-file

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  █████║  ━━━━━━━━━━━━━━━  ║█████
  █████║  ▌ AETHER  v3 ▐  ║█████
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```

# AETHER — Autonomous Robotics Operating System

> AETHER is the autonomous operating system for robots. Plug in and talk to your robot in plain English and ask it to do anything you want.

AETHER connects to whatever hardware is present at startup, discovers every actuator through an interactive GPIO calibration walk, and writes a `physical_map` of every servo and motor by BCM pin. That map feeds into an LLM planner that translates plain-English objectives into the correct hardware action — pin pre-filled, servo type resolved, direction inferred. Motion commands dispatch to GPIO, while a PPO fault-detection network runs concurrently on the 15-dimensional sensor observation vector, detecting and recovering from failures in real time. Every layer — discovery, pin mapping, natural-language planning, execution, fault recovery — runs on a Raspberry Pi with no cloud dependency except the Anthropic API for the planner.

[Demo and docs → aether-robotics.com](https://aether-robotics.com)

---

## Quick Start

```bash
pip install aether-robotics
aether --calibrate
aether --mode agent
```

Calibration walks every safe GPIO pin (BCM 4–27, excluding I2C/SPI/UART), pulses each with a positional servo sweep, and prompts you to label what moved. The result is a `physical_map` saved in your calibration profile and loaded automatically at next startup.

Once calibrated:

```
objective> move the wheel forward for 5 seconds
[PLAN]  [LLM]  servo_cont_wheel
[EXEC]  servo_cont_wheel(speed=50, duration=5)
[OK]    success=True  (5009ms)
```

AETHER discovered the wheel on BCM 17 during calibration, the planner mapped "wheel forward" to the calibrated action, the servo spun for 5 seconds and stopped.

---

## What AETHER Does That Others Don't

- **Discovers the robot.** Calibration walks every GPIO pin, you label what moved, AETHER builds a `physical_map` with BCM pin, device type, and action label for each actuator (unlike ROS/Viam where you configure drivers manually before the system knows what hardware exists).
- **Publishes the Robot Genome.** Every calibrated robot gets a versioned `robot.json` identity card — a stable, portable description of its locomotion class, actuators, and sensors. Capabilities are derived deterministically from the genome (same hardware = same capability set), so skills written for a `differential_drive` genome run on every matching robot without wiring changes. See [docs/robot-genome-v1.md](docs/robot-genome-v1.md) for the published schema.
- **Speaks natural language.** Type plain English; the LLM planner resolves intent against your robot's genome capabilities and dispatches the correct actuator — BCM pin pre-filled, servo type resolved, direction inferred (unlike ROS action servers that require typed message structs and correct namespace knowledge).
- **Detects faults in real time.** DRL-First Hybrid FDIR achieves SFRI 69.99, 100% detection rate, and 100% recovery rate over 6,023 real-hardware steps (unlike threshold-rule systems that require manual parameter tuning per platform and miss novel fault signatures).
- **Improves through use.** Correction traces are logged per step; operational memory and sim-to-real action transfer are on the roadmap (unlike static planners that repeat the same failure mode without feedback).

### Robot Genome

```bash
aether --genome show
```

```
Robot Genome
  ID:         f47ac10b-...
  Locomotion: differential_drive
  Hash:       a3f1d92e...

Capabilities (6)
  drive_backward  drive_forward  emergency_stop  stop  turn_left  turn_right
```

The genome is stored at `configs/robot.json` and auto-migrates from `physical_map` on
first load of a v3.4.x profile. Skills declare `SKILL_REQUIRES = ["drive_forward", ...]`
and AETHER rejects skills the robot's genome cannot satisfy — before any hardware moves.
Full schema, derivation rules, and skill authoring guide: [docs/robot-genome-v1.md](docs/robot-genome-v1.md).

---

## Commands

### Modes

| Flag | Description |
|------|-------------|
| `--mode sim` | Simulation with fault injection against a virtual robot (default) |
| `--mode agent` | Interactive LLM-planned objectives on live hardware; prompts for input |
| `--mode realworld` | Continuous live-hardware FDIR loop — camera + system sensors, no planner |
| `--mode server` | HTTP API on `--port`; accepts `POST /objective` and `GET /health` |
| `--mode dashboard` | Flask web UI on port 5000 with live objective submission and OLED preview |

### Useful Flags

| Flag | When to use |
|------|-------------|
| `--calibrate` | First-time setup — walks every GPIO pin, you label what moves |
| `--recalibrate` | Re-run the full pin walk (e.g. after wiring changes); skips known-empty pins; preserves `robot_id` |
| `--auto-calibrate` | Headless calibration with no interactive prompts |
| `--genome show` | Print the loaded robot genome (locomotion, actuators, capabilities) and exit |
| `--once "objective"` | Run a single objective non-interactively and exit; useful in scripts |
| `--task "objective"` | Task description for `--mode sim` |
| `--schedule "..."` | Scheduled runs: `"every 30s: scan environment"`, `"for 5min: obj"`, `"until 22:00: obj"` |
| `--continuous` | Run `--mode realworld` indefinitely until Ctrl-C |
| `--servo-pin N` | Override the servo GPIO BCM pin for this session (supersedes calibration profile) |
| `--robot {rover_v1,drone_v1}` | Robot config for `--mode sim` (default: `rover_v1`) |
| `--faults {disabled,enabled,heavy}` | Fault injection level for sim/realworld (default: `disabled`) |
| `--scenario TEXT` | Sim scenario: `simple`, `obstacles`, `imu_fault`, `battery`, `compound`, `fault_heavy` |
| `--max-steps N` | Max steps per episode (default: 300) |
| `--seed N` | Random seed for reproducible sim runs (default: 42) |
| `--render` | Print ASCII state render at each sim step |
| `--plots` | Generate matplotlib SFRI/metrics plots after a sim run |
| `--no-learning` | Freeze PPO weights — useful for controlled benchmarking |
| `--port N` | Port for `--mode server` (default: 8080) |
| `--auto-install` | Install missing Python packages without prompting |
| `--auto-update` | Pull the latest version without prompting |
| `--no-install` | Skip the package-install prompt entirely |
| `--no-update` | Skip the update check |
| `--verbose` | Enable debug logging |

---

## Supported Hardware

**Tested and working**

Raspberry Pi 4 Model B · USB camera or picamera2 · GPIO servos (positional or continuous-rotation) · SSD1306 OLED over SPI · Anthropic API (LLM planner and vision)

**Should work, unverified**

Pi Zero 2 W · Pi 5 (requires `rpi-lgpio` in place of `RPi.GPIO`) · PCA9685 I2C 16-channel servo driver · MAVLink flight controllers via USB serial

**In development**

Arduino/ESP32 serial bridge · ArduPilot drone support · multi-robot coordination

---

## Architecture

```
  User input (plain English)
        │
        ▼
  ToolDiscovery ──────────────► physical_map  (saved calibration profile)
        │                                  │
        ▼                                  ▼
  LLMPlanner ◄──── physical_map injected into planner context
        │
        ▼
  NavigationEngine  (L1 camera / L2 GPIO / L3 MAVLink)
        │                         │
        ▼                         ▼
  Hardware (servo/motor/FC)  FaultAgent (PPO, 15-dim obs → fault class)
                                   │
                             detect · recover · log
```

---

## Benchmarks

Real-hardware deployment: Raspberry Pi 4, GPIO servos, live camera, Anthropic API planner.

| Metric | Value | Conditions |
|--------|------:|------------|
| SFRI | **69.99** | 6,023 steps, real hardware |
| MTTR | **1.35 steps** | Mean time to recover from injected fault |
| Detection rate | **100%** | 0 misses, 0 false positives |

> SFRI (Stability Fault Recovery Index) = 35×DR + 25×(1 − MTTR/max\_steps) + 10×RR − 30×FPR. Range 0–70; higher is better.

---

## Roadmap

- ✓ **Phase 1 — Reverse Engineering** — GPIO pin walk, physical_map, LLM-planned hardware control
- �� **Phase 2 — Robot Genome** — versioned `robot.json` schema, deterministic capability derivation, skill portability ([docs/robot-genome-v1.md](docs/robot-genome-v1.md))
- **Phase 3 — Vision-Language Grounding** — "follow the orange cone", scene-grounded navigation, in progress
- **Phase 4 — Operational Memory + Sim-to-Real Action Transfer**
- **Phase 5 — Multi-robot coordination**

---

## Early Access

AETHER is in early access. We're working with a small number of robotics teams and researchers to refine the platform. Email chahelpaatur@aether-robotics.com for access.

---

## Citation

```bibtex
@software{aether2026,
  title   = {AETHER: Autonomous Operating System for Robots},
  author  = {Paatur, Chahel},
  year    = {2026},
  version = {3.4.3},
  url     = {https://aether-robotics.com},
  note    = {DRL-First Hybrid FDIR with physical-map calibration and LLM planning},
}
```

---

AETHER is proprietary software in early access. All rights reserved. © 2026 Chahel Paatur.
