ros2_nmpc package

A ROS 2 package implementing Nonlinear Model Predictive Control (NMPC) for differential drive robots using the Acados solver.

Description

This package provides a ROS 2 node that implements NMPC for trajectory tracking of differential drive robots. It uses the Acados solver for efficient solution of the optimal control problem.

Prerequisites

• ROS 2 (tested on Humble, but should work on other distributions)
• Acados (with Python interface)
• Python 3
• CMake (>= 3.8)

Installation

1. Install ROS 2 and create a workspace:

   mkdir -p ~/ros2_ws/src
   cd ~/ros2_ws/src

2. Clone this repository into your ROS 2 workspace:

   git clone https://github.com/SokhengDin/ROS2-NMPC-ACADOS.git

3. Install Acados following the official installation guide.

4. Update the ACADOS_INSTALL_DIR in CMakeLists.txt to point to your Acados installation directory.

5. Build the package:

   cd ~/ros2_ws
   colcon build --packages-select ros2_nmpc

6. Source the workspace:

   source ~/ros2_ws/install/setup.bash

Usage

1. Configure the NMPC parameters in config/nmpc_diff_params.yaml.

2. Launch the NMPC node:

   ros2 launch ros2_nmpc nmpc_differential_drive_node.launch.py

3. The node will subscribe to /odom for the current robot state and publish velocity commands to /cmd_vel.

Configuration

You can modify the NMPC parameters in config/nmpc_diff_params.yaml. The main parameters are:

• lbx, ubx: State constraints (lower and upper bounds)
• lbu, ubu: Control constraints (lower and upper bounds)
• Q_diag: State cost diagonal
• R_diag: Control cost diagonal
• R_rate_diag: Control rate cost diagonal
• dt: Time step
• num_trajectory_points: Number of points in the reference trajectory
• distance_threshold: Threshold for considering target reached
• target_x, target_y, target_theta: Target pose

Customization

To use this NMPC controller with a different robot model:

1. Modify the differential_drive_model in acados_generated/ to match your robot's dynamics.
2. Update the NMPCDifferentialDrive class in src/nmpc_differential_drive.cpp to use the new model.
3. Adjust the parameters in config/nmpc_diff_params.yaml to suit your robot and control requirements.

Troubleshooting

• If you encounter "file not found" errors during compilation, ensure that all Acados generated files are in the correct location and that the ACADOS_INSTALL_DIR in CMakeLists.txt is set correctly.
• If the node fails to start, check that the Acados solver library libacados_ocp_solver_differential_drive.so is present in the acados_generated/differential_drive/ directory.