5 papers
OIPP: Object-Adaptive Impact Point Predictor for Catching Diverse In-Flight Objects
Ngoc Huy Nguyen, Kazuki Shibata, Takamitsu Matsubara
In this study, we address the problem of in-flight object catching using a quadruped robot with a basket. Our objective is to accurately predict the impact point, defined as the ob…
DeReCo: Decoupling Representation and Coordination Learning for Object-Adaptive Decentralized Multi-Robot Cooperative Transport
Kazuki Shibata, Ryosuke Sota, Shandil Dhiresh Bosch +4
Generalizing decentralized multi-robot cooperative transport across objects with diverse shapes and physical properties remains a fundamental challenge. Under decentralized executi…
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…
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…
Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation
Ing-Sheng Bernard-Tiong, Yoshihisa Tsurumine, Ryosuke Sota +2
Cooperative grasping and transportation require effective coordination to complete the task. This study focuses on the approach leveraging force-sensing feedback, where robots use…