Synthetic Parabolic Trajectories Dataset in Hexapod Robots

Published: 7 December 2023| Version 1 | DOI: 10.17632/cfwy3y76jb.1
Aldo Cervantes Marquez


Parabolic trajectories constitute the primary motion of a robotic leg. Therefore, the data used to train models requires variations to the ideal (proposed) trajectories. Thus, it is essential to generate random sequences based on parabolic trajectories in each degree of freedom so that, collectively, they create a random three-dimensional step. The database comprises three classes of planar movements—two parabolic and one sigmoidal—representing one degree of freedom. Its structure consists of 200 timesteps, indicating the discretization of the continuous trajectory range into 1000 uniformly distributed trajectories across the three classes of movements in each degree of freedom.


Steps to reproduce

To access the data, it is necessary to utilize the Python numpy library, wherein the np.load() function should be employed. This enables the data to be treated as either a matrix or a .csv file.


Universidad Autonoma de Queretaro


Artificial Intelligence, Control System, Robotics, Computer-Based Training


Consejo Nacional de Ciencia y Tecnología