Author

M. Hayashibe

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#artificial intelligence Preprint Sep 2026

SynIL: Leveraging Synergy for Offline Imitation Learning from Imperfect Demonstration Datasets

Synergy-based Imitation Learning is introduced, a novel framework for automated, label-free demonstration quality assessment in offline reinforcement learning and achieves performance comparable to, and in sparse-reward human teleoperation scenarios, superior to, offline reinforcement learning trained on true environme...

Yuto Tanaka, Kyo Kutsuzawa, Martina Doku et al. · 0 citations

Open access Jul 2026

From insect behavior to transferable robot locomotion: inferring embodied locomotor principles from limited data via adversarial inverse reinforcement learning

A data-driven framework based on adversarial inverse reinforcement learning is proposed, which directly learns continuous locomotion control policies from stick insect walking data and infers latent reward structures and control strategies from biological behavioral demonstrations, with potential applications to bio-in...

Yuchen Wang, Thirawat Chuthong, M. Hayashibe et al. · Bioinspiration & Biomimetics · 0 citations

Preprint Aug 2026

LAC: Linear and Angular Compliance for Humanoid Whole-body Control

LAC is presented, a general whole-body controller that simultaneously realizes commanded Linear and Angular Compliance for wrenches applied to the upper body and monotonic modulation over the full range of both stiffness commands, and applicability to teleoperated loco-manipulation tasks.

Yang Liu, Zhongkai Gu, Wei Zhu et al. · 2 citations