Abdelrahman Nashat
Ballbot Simulation System: Modeling, Verification, and Gym Environment Development
Nashat, Abdelrahman; Morsi, Abdelrahman; Hassan, Mohamed M.M.; Abdelrahman, Mustafa
Authors
Abstract
This paper introduces the development of a sophisticated simulation model for the ball-balancing robot (ballbot), implemented as a Gymnasium (Gym) environment in Python. The main purpose of this environment is to facilitate the application of Reinforcement Learning (RL) techniques to effectively control the ballbot system. Initially, a standard ballbot model is created using Solidworks, and a Unified Robot Description Format (URDF) file is generated to precisely capture the dynamics of the ballbot. To validate the model, simulations are performed within MATLAB/Simulink, comparing the ballbot URDF model against its nonlinear mathematical model with a simple PID controller. The simulation results demonstrate that the URDF model accurately represents the ballbot dynamics, exhibiting a comparable response to the mathematical model. Subsequently, the high-fidelity URDF model is integrated into the Gym environment using the Pybullet simulator. The ongoing objective of this research is to utilize the developed ballbot environment for RL-based control design.
Citation
Nashat, A., Morsi, A., Hassan, M. M., & Abdelrahman, M. (2023, November). Ballbot Simulation System: Modeling, Verification, and Gym Environment Development. Presented at 2023 Eleventh International Conference on Intelligent Computing and Information Systems (ICICIS), Cairo, Egypt
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 2023 Eleventh International Conference on Intelligent Computing and Information Systems (ICICIS) |
Start Date | Nov 21, 2023 |
End Date | Nov 23, 2023 |
Acceptance Date | Nov 1, 2023 |
Online Publication Date | Jan 18, 2024 |
Publication Date | Jan 18, 2024 |
Deposit Date | Feb 24, 2024 |
Publicly Available Date | Mar 10, 2025 |
Peer Reviewed | Peer Reviewed |
Pages | 198-204 |
Series Title | International Conference on Intelligent Computing and Information Systems (ICICIS) |
Series Number | 11 |
Series ISSN | 2831-5952 |
ISBN | 9798350322088 |
DOI | https://doi.org/10.1109/ICICIS58388.2023.10391172 |
Public URL | https://hull-repository.worktribe.com/output/4558612 |
Files
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Copyright Statement
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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