3 papers
cs.RO2026
ViSA: Visited-State Augmentation for Generalized Goal-Space Contrastive Reinforcement Learning
Issa Nakamura, Tomoya Yamanokuchi, Yuki Kadokawa +5
Goal-Conditioned Reinforcement Learning (GCRL) is a framework for learning a policy that can reach arbitrarily given goals. In particular, Contrastive Reinforcement Learning (CRL)…
cs.RO2026
CoLF: Learning Consistent Leader-Follower Policies for Vision-Language-Guided Multi-Robot Cooperative Transport
Joachim Yann Despature, Kazuki Shibata, Takamitsu Matsubara
In this study, we address vision-language-guided multi-robot cooperative transport, where each robot grounds natural-language instructions from onboard camera observations. A key c…
cs.RO2025
ICCO: Learning an Instruction-conditioned Coordinator for Language-guided Task-aligned Multi-robot Control
Yoshiki Yano, Kazuki Shibata, Maarten Kokshoorn +1
Recent advances in Large Language Models (LLMs) have permitted the development of language-guided multi-robot systems, which allow robots to execute tasks based on natural language…