End-to-End Design and Validation of a Low-Cost Stewart Platform with Nonlinear Estimation and Control

Fuente: arXiv
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Main Authors: Cinun, Benedictus C. G., Tamba, Tua A., Santjoko, Immanuel R., Wang, Xiaofeng, Gunarso, Michael A., Hu, Bin
Format: Preprint
Published: 2025
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author Cinun, Benedictus C. G.
Tamba, Tua A.
Santjoko, Immanuel R.
Wang, Xiaofeng
Gunarso, Michael A.
Hu, Bin
author_facet Cinun, Benedictus C. G.
Tamba, Tua A.
Santjoko, Immanuel R.
Wang, Xiaofeng
Gunarso, Michael A.
Hu, Bin
contents This paper presents the complete design, control, and experimental validation of a low-cost Stewart platform prototype developed as an affordable yet capable robotic testbed for research and education. The platform combines off the shelf components with 3D printed and custom fabricated parts to deliver full six degrees of freedom motions using six linear actuators connecting a moving platform to a fixed base. The system software integrates dynamic modeling, data acquisition, and real time control within a unified framework. A robust trajectory tracking controller based on feedback linearization, augmented with an LQR scheme, compensates for the platform's nonlinear dynamics to achieve precise motion control. In parallel, an Extended Kalman Filter fuses IMU and actuator encoder feedback to provide accurate and reliable state estimation under sensor noise and external disturbances. Unlike prior efforts that emphasize only isolated aspects such as modeling or control, this work delivers a complete hardware-software platform validated through both simulation and experiments on static and dynamic trajectories. Results demonstrate effective trajectory tracking and real-time state estimation, highlighting the platform's potential as a cost effective and versatile tool for advanced research and educational applications.
format Preprint
id arxiv_https___arxiv_org_abs_2510_22949
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle End-to-End Design and Validation of a Low-Cost Stewart Platform with Nonlinear Estimation and Control
Cinun, Benedictus C. G.
Tamba, Tua A.
Santjoko, Immanuel R.
Wang, Xiaofeng
Gunarso, Michael A.
Hu, Bin
Robotics
Systems and Control
93C10
I.2.9; I.2.8; J.2
This paper presents the complete design, control, and experimental validation of a low-cost Stewart platform prototype developed as an affordable yet capable robotic testbed for research and education. The platform combines off the shelf components with 3D printed and custom fabricated parts to deliver full six degrees of freedom motions using six linear actuators connecting a moving platform to a fixed base. The system software integrates dynamic modeling, data acquisition, and real time control within a unified framework. A robust trajectory tracking controller based on feedback linearization, augmented with an LQR scheme, compensates for the platform's nonlinear dynamics to achieve precise motion control. In parallel, an Extended Kalman Filter fuses IMU and actuator encoder feedback to provide accurate and reliable state estimation under sensor noise and external disturbances. Unlike prior efforts that emphasize only isolated aspects such as modeling or control, this work delivers a complete hardware-software platform validated through both simulation and experiments on static and dynamic trajectories. Results demonstrate effective trajectory tracking and real-time state estimation, highlighting the platform's potential as a cost effective and versatile tool for advanced research and educational applications.
title End-to-End Design and Validation of a Low-Cost Stewart Platform with Nonlinear Estimation and Control
topic Robotics
Systems and Control
93C10
I.2.9; I.2.8; J.2
url https://arxiv.org/abs/2510.22949