sl-perception
f71fdae747
Add saltybot_depth_costmap — a Nav2 costmap2d plugin that converts D435i depth images directly into obstacle markings on both local and global costmaps. Pipeline: 1. Subscribe to /camera/depth/image_rect_raw (16UC1 mm) + camera_info 2. Back-project depth pixels to 3D using pinhole camera intrinsics 3. Transform points to costmap global_frame via TF2 4. Apply configurable height filter (min_height..max_height above ground) 5. Mark obstacle cells as LETHAL_OBSTACLE 6. Inflate neighbours within inflation_radius as INSCRIBED_INFLATED_OBSTACLE Parameters: min_height: 0.05 m — floor clearance (ignores ground returns) max_height: 0.80 m — ceiling cutoff (ignores lights/ceiling) obstacle_range: 3.5 m — max marking distance from camera clearing_range: 4.0 m — max distance processed at all inflation_radius: 0.10 m — in-layer inflation (works before inflation_layer) downsample_factor: 4 — process 1 of N rows+cols (~19k pts @ 640×480) Integration (#478): - Added depth_costmap_layer to local_costmap plugins list - Added depth_costmap_layer to global_costmap plugins list - Plugin registered via pluginlib (plugin.xml) Files: jetson/ros2_ws/src/saltybot_depth_costmap/ CMakeLists.txt, package.xml, plugin.xml include/saltybot_depth_costmap/depth_costmap_layer.hpp src/depth_costmap_layer.cpp jetson/ros2_ws/src/saltybot_bringup/config/nav2_params.yaml (updated) 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.