8 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…
Autonomous Obstacle Removal for Excavators through Policy Learning with Particle Simulation
Yuki Kadokawa, Sandro M. Alcantara Tacora, Taro Abe +4
Autonomous obstacle removal from the ground is an important earthwork task, but this is difficult to automate because an excavator must adapt its excavation trajectories over repea…
Bridged SBI: Correcting Biased Low-Fidelity Posteriors for Cost-Efficient High-Fidelity Inference
Gahee Kim, Yuki Kadokawa, Sandro M. Alcantara Tacora +5
Accurate calibration of particle-based simulators is crucial for robotic earthwork simulation, but analytical calibration is challenging due to this task's highly nonlinear particl…
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)…
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…