A marginalized particle filter interfaces a nominal constant-curvature model with a Gaussian Process bending-stiffness model to enable simultaneous pose estimation and online learning from base reactions in a real soft robot.
Bayesian Inference and Learning in Nonlinear Dynamical Systems: A Framework for Incorporating Explicit and Implicit Prior Knowledge,
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Simultaneous State Estimation and Online Model Learning in a Soft Robotic System
A marginalized particle filter interfaces a nominal constant-curvature model with a Gaussian Process bending-stiffness model to enable simultaneous pose estimation and online learning from base reactions in a real soft robot.