Author

G. Minelli

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Preprint Oct 2026

Learning from Relative Action Credit for Escaping Local Minima

Reinforcement learning holds the promise of robots that learn manipulation skills from interaction alone, without pretrained priors or demonstration data. In practice, on-policy methods such as PPO routinely stall on long-horizon, contact-rich tasks: dense reward shaping carries the policy through stages, yet stitching...

G. Minelli, Giulio Turrisi, Lorenzo Amatucci et al. · 0 citations

Preprint Oct 2026

LocoPilot: Single-Operator Bilateral Teleoperation for Loco-Manipulation Policy Learning

Learning loco-manipulation policies requires demonstrations that capture coordinated base and arm motion on the target embodiment. Robot-free interfaces allow demonstrations to be collected independently of the target robot, increasing flexibility but without directly capturing platform-specific commands, proprioceptio...

A. Langella, G. Minelli, Giovanni B. Dessy et al. · 0 citations