sl-controls
60d8d19342
Implement rate-limiting for velocity commands to prevent jerky motion.
Applies independent acceleration/deceleration limits to linear and angular velocity.
Features:
- Smooth acceleration/deceleration rate limiting
Default: 0.5 m/s² linear, 1.0 rad/s² angular (configurable)
- Independent limits for each velocity component (x, y, z linear; x, y, z angular)
- Calculates maximum change per control cycle: limit * dt
- Clamps velocity changes to stay within acceleration envelope
- 50Hz control frequency with configurable parameters
Algorithm:
- Subscribe to /cmd_vel (target velocity)
- For each component: change = target - current
- Clamp change: |change| ≤ accel_limit * period
- Apply clamped change to current velocity
- Publish smoothed /cmd_vel_smooth
Benefits:
- Prevents jerky motion from sudden velocity jumps
- Protects mechanical systems from shock loads
- Enables gradual speed/direction changes
- Smooth tracking of dynamic targets
Test Coverage:
- 30+ unit tests covering:
- Node initialization and parameter configuration
- Individual component rate limiting (linear, angular)
- Acceleration and deceleration scenarios
- Multi-component simultaneous limiting
- Reaching target velocity after multiple cycles
- Emergency stops and rapid direction changes
- Independent linear vs angular limits
- Realistic scenarios: gradual acceleration, smooth stops, turns while moving,
obstacle avoidance, continuous motion tracking, oscillating targets
Topics:
- Subscribed: /cmd_vel (geometry_msgs/Twist)
- Published: /cmd_vel_smooth (geometry_msgs/Twist)
Config: frequency=50Hz, linear_accel_limit=0.5 m/s², angular_accel_limit=1.0 rad/s²
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.