sl-controls
1c8430e68a
Implements saltybot_pure_pursuit package: - Pure pursuit algorithm for path following with configurable parameters - Lookahead distance (0.5m default) for target point on path - Goal tolerance (0.1m) for goal detection - Heading error correction to reduce speed when misaligned with path - Publishes Twist commands on /cmd_vel_tracked for Nav2 integration - Subscribes to /odom (odometry) and /path (Path trajectory) - Tracks and publishes cross-track error for monitoring Pure pursuit geometry: - Finds closest point on path to robot current position - Looks ahead specified distance along path from closest point - Computes steering angle to follow circular arc to lookahead point - Reduces linear velocity when heading error is large (with correction enabled) - Clamps velocities to configurable maximums Configuration parameters: - lookahead_distance: 0.5m (typical range: 0.1-1.0m) - goal_tolerance: 0.1m (distance to goal before stopping) - heading_tolerance: 0.1 rad (unused but can support in future) - max_linear_velocity: 1.0 m/s - max_angular_velocity: 1.57 rad/s - use_heading_correction: true (reduces speed on large heading errors) Comprehensive test suite: 20+ tests covering: - Geometric calculations (distance, quaternion conversions) - Path following logic (empty path, straight/curved/spiral paths) - Steering calculations (heading errors, velocity limits) - Edge cases and realistic scenarios - Control loop integration - Parameter variations 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.