DDR-opt

DDR-opt is a universal Trajectory Optimization Framework for Differential Drive Robot Class.

The paper is published in T-ASE!

Please visit our project website DDR-opt. If you find this work useful or interesting, please kindly give us a star ⭐, thanks! 😀

Quick Start

Compiling tests passed on ubuntu 18.04, and 20.04 with ros installed. You can just execute the following commands one by one.

Dependence:

sudo apt install ros-${ROS_DISTRO}-tf2-sensor-msgs # noetic or melodic

OSQP and OSQP-Eigen make it easier to modify parameters and are used to solve control problems under velocity and angular velocity control. You can download them from the following two links:

• Download osqp-v0.6.3-src.tar.gz or click here, and then follow the installation instructions
• Download OSQP-eigen v0.8.1.

cd osqp-eigen
mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX:PATH=/usr/local ../
make
sudo make install

NOTE: We may have forgotten other dependencies 😟, sorry! If you could provide missing dependencies, we would greatly appreciate it.

Build

mkdir -p DDRopt_ws/src
cd DDRopt_ws/src
git clone [email protected]:ZJU-FAST-Lab/DDR-opt.git
cd ..
catkin build

Run

You can run any of the following:

roslaunch plan_manager planner_nmpc.launch # for robots controlled by wheel speeds
roslaunch plan_manager planner_sim_unknown.launch # for planning in unknown space
roslaunch plan_manager planner_sim.launch # for robots controlled by linear and angular velocity

You can use 2D Nav Goal to set goal point.

Update

25-07-25

1. Enhanced the 'if_directly_constrain_v_omega' feature. Users can now select between: 1) Constraining linear (v) and angular (omega) velocities independently, or 2) Constraining the product (v * omega) considering wheel speed limits.
2. Reduced the number of ROS messages in the code that do not use topic remapping.
3. Fixed the bug reported in Issue 11. Thanks to SCUTBob for the report!

Citing

The method used in this software are described in the following paper (available on IEEE and arxiv)

@ARTICLE{zhang2024universaltrajectoryoptimizationframework,
  author={Zhang, Mengke and Chen, Nanhe and Wang, Hu and Qiu, Jianxiong and Han, Zhichao and Ren, Qiuyu and Xu, Chao and Gao, Fei and Cao, Yanjun},
  journal={IEEE Transactions on Automation Science and Engineering}, 
  title={Universal Trajectory Optimization Framework for Differential Drive Robot Class}, 
  year={2025},
  volume={22},
  number={},
  pages={13030-13045},
  keywords={Robots;Mobile robots;Kinematics;Trajectory optimization;Planning;Robot kinematics;Computational modeling;Dynamics;Wheels;Tracking;Motion planning;trajectory optimization;differential drive robot class;nonholonomic dynamics},
  doi={10.1109/TASE.2025.3550676}}