6 citations · 6 across the 9 of their papers we have counts for
5 papers · 1 filter
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 Grasping and Lifting
Kazuki Shibata, Ryosuke Sota, Shandil Dhiresh Bosch +3
Generalizing decentralized multi-robot cooperative grasping and lifting across objects with diverse shapes and physical properties remains a fundamental challenge. Under decentrali…
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…