Author: Gonzalo Jesús Paz Delgado, [email protected]

Co-author: J. Ricardo Sánchez Ibáñez, [email protected]

Supervisor: Carlos J. Pérez del Pulgar, [email protected]

Organization: Space Robotics Lab, University of Malaga

• Description
• Installation
• Examples
• Dependencies
• File tree
• Citation

Coupled path and motion planner for Mobile Manipulation (MM), focused on rovers with a restricted arm workspace.

• First, a Fast Marching Method (FMM) based path planner generates a safe trajectory to reach the goal vicinity, avoiding obstacles and non-traversable areas in the scenario. The path planner is able to control the final rover orientation to ensure that the goal is finally reachable by the arm.
• Second, a FMM 3D based motion planner generates the arm joints motion profile, by creating a 3D tunnel-like cost volume surrounding the already computed rover base trajectory. This tunnel makes use of an offline-computed safe workspace of the manipulator, thus ensuring that no self-collision will occur during the planned motion.

Check the Simulation and field tests video.

In order to get this repository together with its submodules, use the following command (Source):

git clone --recursive ADE-Mobile_Manipulation

Then, to install the component and the required packages:

cd ~/ADE-Mobile_Manipulation
chmod u+x install.sh
sudo ./install.sh

There are several unit tests that can be used as examples. To run them:

./runUnitTests

Then, the results will be saved in:

test/unit/data/results

The input for the unit tests (rover and goal poses, maps...) can be modified in:

test/unit/data/input

The unit test results can be viewed using the provided python3 utils. For example, to represent the evolution of the arm during the motion plan:

cd utils/unitTestsViewers/
python3 armFullPlanViewer.py <approach>

Or to represent the base motion plan:

python3 baseMotionPlanViewer.py <approach>

Where <approach> is:

• 0 for end deployment within the coupled approach
• 1 for progressive deployment within the coupled approach
• 2 for beginning deployment within the coupled approach
• 3 for decoupled solution

• OpenCV 3.2.0

• DART 6.9.2

• python3-pip

• mayavi

• PyQt5

• python3-matplotlib

If this work was helpful for your research, please consider citing the following BibTeX entry:

@ARTICLE{author={Paz-Delgado, G.J. and Sánchez-Ibáñez, J.R. and Domínguez, R. and Pérez-Del-Pulgar, C.J. and Kirchner, F. and García-Cerezo, A.}, journal={IEEE Access}, title={Combined path and motion planning for workspace restricted mobile manipulators in planetary exploration}, year={2023}, pages={1-1}, doi={10.1109/ACCESS.2023.3298980}}