Random Force

Random forces, representing unpredictable disturbances in dynamical systems, are a key focus in diverse scientific fields, from modeling biological locomotion to designing robust robotic systems. Current research emphasizes developing methods to infer and incorporate these forces into models, particularly for systems with sparse or noisy data, often employing data-driven path augmentation or random force injection techniques within reinforcement learning frameworks. This work is crucial for improving the accuracy and robustness of simulations and control algorithms across various applications, ranging from predicting robot navigation in complex environments to optimizing the design of soft robotic manipulators.