Technology Introduction:
This study presents the design and implementation of a quadruped robot platform supporting Sim-to-Real reinforcement learning (RL) applications. The system encompasses electromechanical hardware design, kinematic modeling, simulation environment construction, and RL-based control training. The platform is intended as a locally developed solution for academic research in Taiwan, offering an affordable and open alternative to foreign commercial robots with limited access to low-level controls.
Industry Applicability:
The quadruped robot has high potential to be applicable for industrial inspection tasks to resolve the labor storage problems.