sl-controls
432d5cb267
Adds saltybot_follower ROS2 package — proportional person-following controller that bridges sl-jetson's /person/target detections to Nav2 /cmd_vel, with the cmd_vel_bridge_node (PR #46) providing safety wrapping. Controller features: - Proportional control: linear.x ∝ distance error, angular.z ∝ bearing - Follow distance: 1.5m default with ±0.3m dead zone (no jitter at target) - Max speed: 0.5 m/s linear, 1.0 rad/s angular (conservative for balance) - Obstacle override: zeroes forward cmd_vel when Nav2 local costmap detects obstacle in forward corridor; turning still allowed - Lost-target state machine: FOLLOWING → person visible STOPPING → lost > 2s, publish zero SEARCHING → lost > 5s, slow rotation (0.3 rad/s) to re-acquire - Mode integration: follow_enabled param (toggle via ros2 param set) independently gates the controller; cmd_vel bridge gates on md=2 Deliverables: saltybot_follower/person_follower_node.py — ROS2 node (314 lines) config/person_follower_params.yaml — all params documented launch/person_follower.launch.py — all params as launch args test/test_person_follower.py — 53 pytest tests, no ROS2 package.xml / setup.py / setup.cfg — package metadata Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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
docs/pinout.md— GPIO/I2C/UART pinout for all peripheralsdocs/power-budget.md— 10W power envelope analysis
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.