This work presents Reinforcement Learning algorithms for controlling the Cable-Driven Parallel Robot (4 cables, underconstrained). The work evaluates DDPG, PPO and TRPO algorithms on a simple robot model, providing a solid foundation for future research and experiments on a real cable-suspended robot.
Sovereign AI for smart, self-learning buildings • Edge-native • 25–35 % energy savings
A unified framework for drone simulation, control, and planning combining RL, classical PID, and inspection planning.
Full locomotion stack for the Unitree Go2: PPO policy for velocity-to-joint-position mapping, PD torque controller, and two guidance loop strategies for position tracking in Isaac Gym.
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