Use VVCM and stable forward kinematics to predict object position for multi-robot transportation system with a deformable sheet.
Project description
VVCM
C++ and Python project for multi-robot transporting system with a deformable sheet, use virtual variable cables model (VVCM) to model the system.
Citation
If you use the forward kinematics algorithm, please cite the following paper (bibtex):
@article{ma2026stable,
title = {Stable Kinematics for Multi-Robot Collaborative Transporting System with a Deformable Sheet},
author = {Ma, Wenyao and Hu, Jiawei and Li, Jiamao and Yi, Jingang and Xiong, Zhenhua},
year = 2026,
journal = {IEEE Transactions on Robotics},
volume = {<To be assigned>},
pages = {<To be assigned>},
doi={10.1109/TRO.2026.3653870}
}
The paper is waiting for publication, early access version can be found here.
Or
@article{hu2024forward,
title = {Forward Kinematics of Object Transporting by a Multi-Robot System With a Deformable Sheet},
author = {Hu, Jiawei and Liu, Wenhang and Yi, Jingang and Xiong, Zhenhua},
year = 2024,
journal = {IEEE Robotics and Automation Letters},
volume = {9},
number = {4},
pages = {3459--3466}
}
If you are interested in the VVCM itself, please cite the following paper (bibtex):
@article{hu2022multirobot,
title = {Multi-Robot Object Transport Motion Planning With a Deformable Sheet},
author = {Hu, Jiawei and Liu, Wenhang and Zhang, Heng and Yi, Jingang and Xiong, Zhenhua},
year = 2022,
journal = {IEEE Robotics and Automation Letters},
volume = {7},
number = {4},
pages = {9350--9357}
}
Installation
C++ Library
The most convenient way to use the C++ library is to copy the code and include it in your project.
Eigen version 3.4 or later is required; otherwise, you may need to modify
CMakeLists.txt.
We do not provide pre-built binaries for the C++ library, and have not yet provided a vcpkg or conan package.
Python Package
From PyPI
You can install the package from PyPI using pip:
pip install VVCM
PyPI hosts the following pre-built wheels:
- Linux:
x86_64,aarch64 - Windows:
AMD64 - macOS:
arm64
Only CPython wheels are provided. If you use PyPy, please build from source.
From Release
In the Release of the repository, you can find pre-built binaries for various platforms:
- Linux:
x86_64,aarch64 - Windows:
AMD64 - macOS:
arm64
Only CPython wheels are provided. If you use PyPy, please build from source.
Build From Source
1. Prerequisites
-
Windows:
-
Ubuntu:
-
macOS:
-
Other Linux distributions: Please modify the installation scripts of Ubuntu.
2. Install dependencies
python -m pip install numpy nanobind scikit-build-core[pyproject]
python -m pip install matplotlib scipy
3. Install the package
python -m pip install --no-build-isolation -v .
Usage
C++ Library
Use stable forward kinematics algorithm to compute the object pose given robot formation and deformable sheet:
#include <iostream>
#include <Eigen/Dense>
#include "VVCM_FK.hpp"
using namespace VVCM;
int main()
{
int N = 4; // number of robots
float zr = 1000.0; // height of the holding points (unit: mm)
MatrixXf Rn(4, 2); // robot formation (x, y) coordinates (unit: mm)
Rn << 213.7, 122.7,
804.6, 37.2,
904.0, 550.0,
439.3, 715.9;
MatrixXf Vn(4, 2); // shape of the deformable sheet (x, y) coordinates (unit: mm)
Vn << -316.1, -421.9,
803.4, -384.1,
746.1, 712.8,
-367.3, 664.2;
std::cout << "----------------------" << std::endl;
VVCM_FK a(N, zr, Vn); // initialize the VVCM_FK object
a.update_stable_solutions(Rn); // compute the stable forward kinematics
// M: the number of stable solutions found
std::cout << "M: " << a.M << std::endl;
if (a.M == 0)
{
std::cout << "No stable solution found." << std::endl;
return 0;
}
// Po: object pose (x, y, z) coordinates for each stable solution (unit: mm)
std::cout << "Po: " << std::endl;
for (const auto &po : a.Po)
{
std::cout << po.transpose() << std::endl;
}
// Vo: deformable sheet vertex (x, y) coordinates for each stable solution (unit: mm)
std::cout << "Vo: " << std::endl;
for (const auto &vo : a.Vo)
{
std::cout << vo.transpose() << std::endl;
}
std::cout << "----------------------" << std::endl;
return 0;
}
If everything is set up correctly, you should see output similar to the following:
----------------------
M: 2
Po:
568.812 324.726 336.736
557.931 341.231 337.246
Vo:
238.618 125.024
208.799 152.534
----------------------
Python Package
Use stable forward kinematics algorithm to compute the object pose given robot formation and deformable sheet:
import numpy as np
from VVCM import VVCM_FK
def test_VVCM_FK():
N = 4 # number of robots
zr = 1000.0 # height of the holding points (unit: mm)
# robot formation (x, y) coordinates (unit: mm)
Rn = np.array(
[
[213.7, 122.7],
[804.6, 37.2],
[904.0, 550.0],
[439.3, 715.9],
]
)
# shape of the deformable sheet (x, y) coordinates (unit: mm)
Vn = np.array(
[
[-316.1, -421.9],
[803.4, -384.1],
[746.1, 712.8],
[-367.3, 664.2],
]
)
print("----------------------")
a = VVCM_FK(N, zr, Vn) # initialize the VVCM_FK object
a.update_stable_solutions(Rn) # compute the stable forward kinematics
# M: the number of stable solutions found
print(f"M: {a.M}")
if a.M == 0:
print("No stable solution found.")
return
# Po: object pose (x, y, z) coordinates for each stable solution (unit: mm)
print("Po: ")
for po in a.Po:
print(po)
# Vo: deformable sheet vertex (x, y) coordinates for each stable solution (unit: mm)
print("Vo: ")
for vo in a.Vo:
print(vo)
print("----------------------")
if __name__ == "__main__":
test_VVCM_FK()
If everything is set up correctly, you should see output similar to the following:
----------------------
M: 2
Po:
[568.8123 324.72644 336.73608]
[557.9307 341.23087 337.2464 ]
Vo:
[238.6181 125.02439]
[208.79898 152.53357]
----------------------
Project details
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