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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.