Author

Yutaka Matsuo

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Preprint Oct 2026

Reinforcement Learning Based Multi-Terrain Adaptive Whole-Body Control for a Quadruped Manipulator

Legged robots equipped with manipulators offer promising capabilities for loco-manipulation tasks in unstructured environments. However, achieving task-consistent end-effector behavior during locomotion remains challenging due to terrain-induced disturbances and the strong coupling between locomotion and manipulation,...

Yan-Zhou Jin, Fei Suo, Chang Liu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Improving Cross-embodiment Transfer in Latent Action Models with Action-Similarity Supervision

This work evaluates cross-embodiment transfer on RoboTwin 2.0 in a controlled setup, two bimanual robots demonstrate disjoint task sets, a policy is trained on all the demonstrations, and each robot is evaluated closed-loop on the tasks only the other demonstrated.

Maxime Alvarez, Renzo Caballero, T. Matsushima et al. · 1 citation

Preprint Aug 2026

DREAM: Deployment-Time Demonstration Generation via Real-to-Sim for Scalable Policy Adaptation

DREAM is presented, a framework that generates fine-tuning data for a pretrained VLA from a captured workspace and a language instruction, without requiring a task-specific human demonstration, and whether it can serve as a scalable data-collection system for the deployment workspace.

Makoto Sato, T. Matsushima, Yutaka Matsuo et al. · 2 citations