sl-controls
ca95489b1d
Complete autonomous navigation stack for SaltyBot: - SLAM Toolbox: online_async 2D LIDAR SLAM from RPLIDAR A1M8 - RealSense D435i: depth → pointcloud → costmap obstacle layer - Nav2 stack: controllers, planners, behavior server, lifecycle management - DWB planner: tuned for 20km/h (5.5 m/s) max velocity operation - VESC odometry bridge: motor telemetry → nav_msgs/Odometry - Costmap integration: LIDAR + depth for global + local costmaps - TF tree: complete setup with base_link→laser, camera_link, odom - Goal interface: /navigate_to_pose action for autonomous goals Configuration: - slam_toolbox_params: loop closure, scan matching, fine/coarse search - nav2_params: AMCL, controllers, planners, behavior trees, lifecycle - Global costmap: static layer + LIDAR obstacle layer + inflation - Local costmap: rolling window + LIDAR + RealSense depth + inflation - DWB planner: 20 vx samples, 40 theta samples, 1.7s horizon Nodes and launch files: - vesc_odometry_bridge: integrates motor RPM to wheel odometry - nav2_slam_bringup: main integrated launch entry point - depth_to_costmap: RealSense depth processing pipeline - odometry_bridge: VESC telemetry bridge Hardware support: - RPLIDAR A1M8: 5.5 Hz, 12m range, 360° omnidirectional - RealSense D435i: 15 Hz RGB-D, 200 Hz IMU, depth range 5m - VESC Flipsky FSESC 4.20: dual motor control via UART - SaltyBot 2-wheel balancer: 0.35m radius, hoverboard motors Co-Authored-By: Claude Haiku 4.5 <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.