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.

翻译：本文介绍了一种低成本Stewart平台原型机的完整设计、控制及实验验证，该平台旨在为科研与教育提供经济实用且功能完备的机器人测试平台。该平台采用商用现货组件结合3D打印与定制加工部件，通过六个连接动平台与固定基座的线性执行器实现完整的六自由度运动。系统软件在统一框架内集成了动力学建模、数据采集与实时控制功能。基于反馈线性化并结合LQR方案增强的鲁棒轨迹跟踪控制器，可补偿平台非线性动力学特性以实现精确运动控制。同时，扩展卡尔曼滤波器融合IMU与执行器编码器反馈，在传感器噪声与外部干扰下提供准确可靠的状态估计。与以往仅侧重建模或控制等单一环节的研究不同，本研究通过静态与动态轨迹的仿真和实验验证，构建了完整的硬件-软件一体化平台。实验结果证明了平台在轨迹跟踪与实时状态估计方面的有效性，凸显其作为经济高效、多功能的先进研究与教育工具的潜力。