amcl 0.1.2
AMCL Python Bindings
Requires Python: <3.14,>=3.8

# AMCL Python Bindings

[![Python](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org)
[![C++17](https://img.shields.io/badge/c%2B%2B-17-blue.svg)](https://en.wikipedia.org/wiki/C%2B%2B17)
[![License: GPLv3](https://img.shields.io/badge/License-GPLv3-yellow.svg)](https://www.gnu.org/licenses/gpl-3.0.en.html)
[![Build](https://github.com/damanikjosh/amcl_python/actions/workflows/build.yml/badge.svg)](https://github.com/damanikjosh/amcl_python/actions/workflows/build.yml)

Python bindings for Adaptive Monte Carlo Localization (AMCL) adapted from the [Nav2 AMCL](https://github.com/ros-navigation/navigation2/tree/main/nav2_amcl).

Vibe-coded with love ❤️

## 📦 Installation

You can install the package using pip:
```bash
pip install amcl
```

Or install from source:
```bash
git clone https://github.com/damanikjosh/amcl_python.git
cd amcl_python
pip install -e .
```

## 🎯 Quick Start

### Basic Usage

```python
import amcl
import numpy as np

# Create motion and laser parameters
motion_params = amcl.MotionParameters(
    alpha1=0.1,
    alpha2=0.1,
    alpha3=0.1,
    alpha4=0.1,
    alpha5=0.1
)
laser_params = amcl.LaserParameters(
    z_hit=0.5,
    z_short=0.05,
    z_max=0.05,
    z_rand=0.5,
    sigma_hit=0.2,
    lambda_short=0.1,
    chi_outlier=0.05,
    max_beams=60
)

# Create AMCL localizer
localizer = amcl.AMCL(
    min_particles=100,
    max_particles=500,
    alpha_slow=0.001,
    alpha_fast=0.1,
    motion_params=motion_params,
    laser_likelihood_max_dist=2.0,
    laser_params=laser_params,
    robot_model_type="differential"
)

# Create occupancy grid map
grid_data = [[0 for _ in range(100)] for _ in range(100)]
grid_data[50][50] = 100  # Add obstacle
grid = amcl.create_occupancy_grid_from_list(grid_data, 0.1, -5.0, -5.0)

# Set map and initial pose
localizer.set_map(grid)
initial_pose = amcl.Vector3D(0.0, 0.0, 0.0)
initial_cov = amcl.Matrix3D()
localizer.set_initial_pose(initial_pose, initial_cov)

# Set laser pose relative to robot base
localizer.set_laser_pose(amcl.Vector3D(0.0, 0.0, 0.0))

# Update with laser scan
ranges = [[i * 0.1, i * 0.017] for i in range(181)]  # [range, bearing] pairs
scan = amcl.create_laser_scan_from_list(ranges, 10.0)
odom_pose = amcl.Vector3D(0.1, 0.0, 0.0)

localizer.update(scan, odom_pose)
pose = localizer.get_pose_mean()
print(f"Estimated pose: ({pose.x:.3f}, {pose.y:.3f}, {pose.theta:.3f})")
```

## 📚 API Reference

### Core Classes

- **`AMCL`**: Main localization class implementing particle filter
- **`Vector3D`**: 3D vector for poses (x, y, theta)
- **`Matrix3D`**: 3x3 matrix for covariances  
- **`LaserScan`**: Laser scanner data structure
- **`OccupancyGrid`**: 2D occupancy grid map
- **`MotionParameters`**: Robot motion model parameters
- **`LaserParameters`**: Laser sensor model parameters

### Utility Functions

- **`create_laser_scan_from_list()`**: Create LaserScan from Python lists
- **`create_occupancy_grid_from_list()`**: Create OccupancyGrid from Python lists
- **`get_version()`**: Get library version

### NumPy Integration (amcl_numpy module)

- **`create_occupancy_grid_from_numpy()`**: Create OccupancyGrid from NumPy array
- **`create_laser_scan_from_numpy()`**: Create LaserScan from NumPy array  
- **`occupancy_grid_to_numpy()`**: Convert OccupancyGrid to NumPy array
- **`laser_scan_to_numpy()`**: Convert LaserScan to NumPy array

## 📄 License

This project is licensed under the GPLv3 License - see the [LICENSE](LICENSE) file for details.

## 🙏 Acknowledgments

- **Nav2 Team**: Original AMCL implementation
- **ROS Community**: Foundational robotics algorithms
- **nanobind**: Excellent Python binding framework
- **Claude Sonnet 4**: For helping with code generation