sl-controls 783dedf4d4 feat(#158): docking station auto-return with ArUco/IR detection and visual servo
Two new ROS2 packages implementing Issue #158:

saltybot_docking_msgs (ament_cmake)
- DockingStatus.msg: stamp, state, dock_detected, distance_m, lateral_error_m,
  battery_pct, charging, aligned
- Dock.srv / Undock.srv: force + resume_mission flags

saltybot_docking (ament_python, 20 Hz)
- dock_detector.py: ArucoDetector (cv2.aruco PnP → DockPose) + IRBeaconDetector
  (EMA envelope with amplitude threshold); both gracefully degrade if unavailable
- visual_servo.py: IBVS proportional controller — v = k_lin×(d−target),
  ω = −k_ang×yaw; aligned when |lateral| < 5mm AND d < contact_distance
- charge_monitor.py: edge-triggered events (CHARGING_STARTED/STOPPED,
  THRESHOLD_LOW at 15%, THRESHOLD_HIGH at 80%)
- docking_state_machine.py: 7-state FSM (IDLE→DETECTING→NAV2_APPROACH→
  VISUAL_SERVO→CONTACT→CHARGING→UNDOCKING); mission_resume signal on
  auto-dock cycle; contact retry on timeout; lost-detection timeout
- docking_node.py: 20Hz ROS2 node; Nav2 NavigateToPose action client (optional);
  /saltybot/dock + /saltybot/undock services; /saltybot/docking_cmd_vel;
  /saltybot/resume_mission; /saltybot/docking_status
- config/docking_params.yaml, launch/docking.launch.py

Tests: 64/64 passing (IRBeaconDetector, VisualServo, ChargeMonitor,
DockingStateMachine — all state transitions and guard conditions covered)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-02 10:19:22 -05:00
..

Jetson Nano — AI/SLAM Platform Setup

Self-balancing robot: Jetson Nano dev environment for ROS2 Humble + SLAM stack.

Stack

Component Version / Part
Platform Jetson Nano 4GB
JetPack 4.6 (L4T R32.6.1, CUDA 10.2)
ROS2 Humble Hawksbill
DDS CycloneDDS
SLAM slam_toolbox
Nav Nav2
Depth camera Intel RealSense D435i
LiDAR RPLIDAR A1M8
MCU bridge STM32F722 (USB CDC @ 921600)

Quick Start

# 1. Host setup (once, on fresh JetPack 4.6)
sudo bash scripts/setup-jetson.sh

# 2. Build Docker image
bash scripts/build-and-run.sh build

# 3. Start full stack
bash scripts/build-and-run.sh up

# 4. Open ROS2 shell
bash scripts/build-and-run.sh shell

Docs

Files

jetson/
├── Dockerfile              # L4T base + ROS2 Humble + SLAM packages
├── docker-compose.yml      # Multi-service stack (ROS2, RPLIDAR, D435i, STM32)
├── README.md               # This file
├── docs/
│   ├── pinout.md           # GPIO/I2C/UART pinout reference
│   └── power-budget.md     # Power budget analysis (10W envelope)
└── scripts/
    ├── entrypoint.sh       # Docker container entrypoint
    ├── setup-jetson.sh     # Host setup (udev, Docker, nvpmodel)
    └── build-and-run.sh    # Build/run helper

Power Budget (Summary)

Scenario Total
Idle 2.9W
Nominal (SLAM active) ~10.2W
Peak 15.4W

Target: 10W (MAXN nvpmodel). Use RPLIDAR standby + 640p D435i for compliance. See docs/power-budget.md for full analysis.