Effective 2026-04-03: STM32F722 flight controller no longer used. New architecture: - ESP32 BALANCE: PID balance loop - ESP32 IO: motors, sensors, comms Updated: CLAUDE.md, TEAM.md, docs/AGENTS.md, docs/SALTYLAB.md Legacy src/ STM32 firmware is archived — not extended. Source code migration pending ESP32 hardware spec from max. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2.8 KiB
SaltyLab — Ideal Team
Project
Self-balancing two-wheeled robot using two ESP32 boards (BALANCE + IO), hoverboard hub motors, Jetson Orin for AI/SLAM.
⚠️ ARCHITECTURE CHANGE (2026-04-03): Mamba F722S (STM32F722) and BlackPill retired. Replaced by ESP32 BALANCE (PID loop) + ESP32 IO (motors/sensors/comms).
Current Status
- Hardware: ESP32 BALANCE + ESP32 IO replacing STM32 FC — details from max incoming
- Firmware: ESP32 firmware TBD; legacy STM32 code in
src/is archived - STM32 blocker (resolved/irrelevant): USB CDC bug was STM32-specific — no longer applies
Roles Needed
1. Embedded Firmware Engineer (Lead)
Must-have:
- Deep STM32 HAL experience (F7 series specifically)
- USB OTG FS / CDC ACM debugging (TxState, endpoint management, DMA conflicts)
- SPI + UART + USB coexistence on STM32
- PlatformIO or bare-metal STM32 toolchain
- DFU bootloader implementation
Nice-to-have:
- Betaflight/iNav/ArduPilot codebase familiarity
- PID control loop tuning for balance robots
- FOC motor control (hoverboard ESC protocol)
Why: The immediate blocker is a USB peripheral conflict. Need someone who's debugged STM32 USB issues before — this is not a software logic bug, it's a hardware peripheral interaction issue.
2. Control Systems / Robotics Engineer
Must-have:
- PID tuning for inverted pendulum / self-balancing systems
- Complementary filter / Kalman filter for IMU sensor fusion
- Real-time control loop design (1kHz+)
- Safety system design (tilt cutoff, watchdog, arming sequences)
Nice-to-have:
- Hoverboard hub motor experience
- ELRS/CRSF RC protocol
- ROS2 integration
Why: Once USB is fixed, the balance loop needs real-world tuning. PID gains, filter coefficients, motor response curves, safety margins — all need someone with hands-on balance bot experience.
3. Perception / SLAM Engineer (Phase 2)
Must-have:
- Jetson Nano / NVIDIA Jetson platform
- Intel RealSense D435i depth camera
- RPLIDAR integration
- SLAM (ORB-SLAM3, RTAB-Map, or similar)
- ROS2
Nice-to-have:
- Person tracking / following
- Obstacle avoidance
- Nav2 stack
Why: Phase 2 goal is autonomous navigation. Jetson Nano with RealSense + RPLIDAR for indoor mapping and person following.
Hardware Reference
| Component | Details |
|---|---|
| FC | MAMBA F722S (STM32F722RET6, MPU6000) |
| Motors | 2x 8" pneumatic hoverboard hub motors |
| ESC | Hoverboard ESC (EFeru FOC firmware) |
| Battery | 36V pack |
| RC | BetaFPV ELRS 2.4GHz TX + RX |
| AI Brain | Jetson Nano + Noctua fan |
| Depth | Intel RealSense D435i |
| LIDAR | RPLIDAR A1M8 |
| Spare IMUs | BNO055, MPU6050 |
Repo
- Gitea: https://gitea.vayrette.com/seb/saltylab-firmware
- Design doc:
projects/saltybot/SALTYLAB.md - Bug doc:
USB_CDC_BUG.md