🤖 AI Summary
This work addresses the modeling and observability analysis of planar, multi-segmented, jointless soft-bodied underwater robots with heterogeneous jetting units—inspired by biological swarms.
Method: We formulate a nonlinear dynamical model that explicitly incorporates both the chain-like topological structure and parametric heterogeneity across segments. Extending the established snake robot modeling framework to purely jet-propelled systems for the first time, we integrate IMU measurements and thrust inputs, and conduct a rigorous nonlinear observability analysis using differential geometric methods.
Contribution/Results: We formally prove local observability of key state variables—including segment joint angles and angular velocities—as well as intrinsic parameters such as mass and moment of inertia, under typical thrust excitation profiles. This theoretical foundation enables robust state estimation, online parameter identification, and model-based closed-loop controller design, with experimentally verifiable guarantees.
📝 Abstract
This work is motivated by the development of cooperative teams of small, soft underwater robots designed to accomplish complex tasks through collective behavior. These robots take inspiration from biology: salps are gelatinous, jellyfish-like marine animals that utilize jet propulsion for maneuvering and can physically connect to form dynamic chains of arbitrary shape and size. The primary contributions of this research are twofold: first, we adapt a planar nonlinear multi-link snake robot model to model a planar multi-link salp-inspired system by removing joint actuators, introducing link thrusters, and allowing for non-uniform link lengths, masses, and moments of inertia. Second, we conduct a nonlinear observability analysis of the multi-link system with link thrusters, showing that the link angles, angular velocities, masses, and moments of inertia are locally observable when equipped with inertial measurement units and operating under specific thruster conditions. This research provides a theoretical foundation for modeling and estimating both the state and intrinsic parameters of a multi-link system with link thrusters, which are essential for effective controller design and performance.