Precise Control of Soft Robots Amidst Uncertain Environmental Contacts and Forces

Recent studies have reported on the remarkable ability of bioinspired soft robots to exhibit dexterous and contact-friendly motions. However, for these robots with deformable bodies, it is extremely challenging to achieve precise and robust control when undergoing uncertain forces and contact in the environment. In this work, we take a first step to address this issue for slender pneumatic soft robots by proposing a comprehensive modeling and control framework. Our framework employs a fully parametrized model that accurately describes both robot configurations and distributed forces using Hermite interpolation. Leveraging this model, we further establish an estimation algorithm that can infer complete robot configurations and distributed external forces from limited motion data, enabling perception of contact locations and forces. Integrating this model and estimator, our control framework achieves precise robot motion control under diverse forces, with the average trajectory tracking error within 0.3 mm. It also detects and adapts to uncertain contact, demonstrated in tests of automatic obstacle avoidance and precise grasping. This framework holds promise for various applications such as environmental exploration and safe manipulation, where compliant interaction with the environment is required.