pymentor 0.1.1

A package to implement a computational model of Mentor didactic robotic arm.

Pymentor

Mentor is a Python library to implement a computational model of the Mentor Didactic Robotic Arm. This model was first published in the work A Genetic Approach for Trajectory Optimization Applied to a Didactic Robot. The library includes:

• Direct kinematics based on Denavit-Hartenberg parameters, where variables represented in the cartesian coordinate space are transformed to joint space.
• Inverse kinematics to encounter joint angles based on position and orientation matrix.
• Exception and error treatment in case of impossible position/orientation pairs.
• Method to deal with alpha, beta and gamma angles to encounter orientation 3x3 matrix based on XYZ angles.

Installation

Use the package manager pip to install pymentor.

pip install pymentor

Usage

Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

import numpy as np
from pymentor import Mentor
# direct kinematics example
angles = [np.pi/6]*5
robot = Mentor()
pos, rot = robot.get_position(angles)
# pos is 4x1 vector 
# rot is 3x3 rotation matrix
       
pos = np.array([24.21323027, 13.97951501, -17.07885504, 1.0])
rot = np.array([[0.59049287, 0.23642905, -0.77163428],
    [-0.23642905, -0.86349762, -0.44550326],
    [-0.77163428, 0.44550326, -0.4539905 ]])
# pos is 4x1 vector 
# rot is 3x3 rotation matrix
angles = robot.get_angles(pos,rot)


# creating rotational matrix from alpha-beta-gamma angles
rot = robot.get_orientation(np.pi/6, np.pi/6, np.pi/6)

Contributing

Any contributions you make are greatly appreciated. To contribute please follow this steps:

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/new_feature)
3. Commit your Changes (git commit -m 'commit-tag: commit-description')
4. Push to the Branch (git push origin feature/new_feature)
5. Open a Pull Request

License

General Public License version 3.0 GPL-3.0

Contact

Oscar Schmitt Kremer - Linkedin Email

Project Link: pymentor Repository

References

O. S. Kremer, M. A. B. Cunha, F. S. Moraes, S. S. Schiavon. A Genetic Apporach for Trajectory Optimization Applied to a Didactic Robot 2019 Latin American Robotics Symposium. 2019. doi:10.1109/LARS-SBR-WRE48964.2019.00049