sl-perception bd9cb6da35 feat(perception): lane/path edge detector (Issue #339)
Adds Canny+Hough+bird-eye perspective pipeline for detecting left/right
path edges from the forward camera.  Pure-Python helper (_path_edges.py)
is fully tested; ROS2 node publishes PathEdges on /saltybot/path_edges.

- saltybot_scene_msgs/msg/PathEdges.msg — new message
- saltybot_scene_msgs/CMakeLists.txt    — register PathEdges.msg
- saltybot_bringup/_path_edges.py       — PathEdgeConfig, PathEdgesResult,
                                          build/apply_homography, canny_edges,
                                          hough_lines, classify_lines,
                                          average_line, warp_segments,
                                          process_frame
- saltybot_bringup/path_edges_node.py  — ROS2 node (sensor_msgs/Image →
                                          PathEdges, parameters for all
                                          tunable Canny/Hough/birdseye params)
- test/test_path_edges.py              — 38 tests, 38 passing
- setup.py                             — add path_edges console_script

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-03 11:33:22 -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.