Task-level ILC learns flying knot rope manipulation from one demo, achieving 100% success within 10 trials on 7 rope types with 2-5 trial transfers.
Gill, Walter Murray, and Michael A
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Hybrid ME-DDP variants combine deterministic DDP with inverse-Hessian sampling to improve success rates over pure DDP and MPPI in robotic navigation under non-convex costs.
citing papers explorer
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Learning Dynamic Rope Manipulation Using Task-Level Iterative Learning Control
Task-level ILC learns flying knot rope manipulation from one demo, achieving 100% success within 10 trials on 7 rope types with 2-5 trial transfers.
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Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control
Hybrid ME-DDP variants combine deterministic DDP with inverse-Hessian sampling to improve success rates over pure DDP and MPPI in robotic navigation under non-convex costs.