sl-perception
b74307c58a
AMCL-based autonomous navigation on pre-built static maps, wired to VESC CAN differential-drive odometry (/odom, Issue #646) and RPLiDAR (/scan) as the primary sensor sources. New files (saltybot_nav2_slam): - config/amcl_nav2_params.yaml — complete Nav2 + AMCL parameter file with inline global/local costmap configs (required by nav2_bringup): · AMCL: DifferentialMotionModel, 500–3000 particles, z-weights=1.0, odom_frame=/odom, scan_topic=/scan · Global costmap: static_layer + obstacle_layer (LiDAR) + inflation_layer (0.55m radius) · Local costmap: 4m rolling window, obstacle_layer (LiDAR) + inflation_layer, global_frame=odom · DWB controller: 1.0 m/s max, diff-drive constrained (vy=0) · NavFn A* planner · Recovery: spin + backup + wait · Lifecycle managers for localization and navigation - launch/nav2_amcl_bringup.launch.py — orchestrates: 1. sensors.launch.py (RealSense + RPLIDAR, conditional) 2. odometry_bridge.launch.py (VESC CAN → /odom) 3. nav2_bringup localization_launch.py (map_server + AMCL) 4. nav2_bringup navigation_launch.py (full nav stack) Exposes: map, use_sim_time, autostart, params_file, include_sensors - maps/saltybot_map.yaml — placeholder map descriptor (0.05m/cell) - maps/saltybot_map.pgm — 200×200 P5 PGM, all free space (10m×10m) - test/test_nav2_amcl.py — 38 unit tests (no ROS2 required): params structure, z-weight sum, costmap layers, DWB/NavFn validity, recovery behaviors, PGM format, launch file syntax checks Updated: - saltybot_bringup/launch/nav2.launch.py — adds nav_mode argument: nav_mode:=slam (default, existing RTAB-Map behaviour unchanged) nav_mode:=amcl (new, delegates to nav2_amcl_bringup.launch.py) - saltybot_nav2_slam/setup.py — installs new launch, config, maps - saltybot_nav2_slam/package.xml — adds nav2_amcl, nav2_map_server, nav2_behaviors, dwb_core, nav2_navfn_planner exec_depends All 58 tests pass (38 new + 20 from Issue #646). 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.