Floating Platform

Floating platforms, particularly those used to simulate microgravity environments for space robotics research, are the focus of ongoing investigation aimed at improving their control and trajectory optimization. Current research emphasizes advanced control algorithms, such as Model Predictive Control (MPC) and reinforcement learning techniques like Proximal Policy Optimization (PPO), to address challenges posed by uncertain dynamics and actuator constraints (e.g., on/off thrusters). These advancements are crucial for enabling precise manipulation and autonomous navigation of floating platforms in space-related applications like active debris removal and scientific experiments in zero-gravity.