A human-in-the-loop Pareto optimization framework characterizes trade-offs between performance and challenge in assist-as-needed motor training, enabling protocol design and fair evaluation even when users cannot complete tasks unaided.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
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.
citing papers explorer
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Human-in-the-Loop Pareto Optimization: Trade-off Characterization for Assist-as-Needed Training and Performance Evaluation
A human-in-the-loop Pareto optimization framework characterizes trade-offs between performance and challenge in assist-as-needed motor training, enabling protocol design and fair evaluation even when users cannot complete tasks unaided.
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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.