9 papers
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)…
Robust Sim-to-Real Cloth Untangling through Reduced-Resolution Observations via Adaptive Force-Difference Quantization
Yoshihisa Tsurumine, Yuki Kadokawa, Kohei Hayashi +2
Robotic cloth untangling requires progressively disentangling fabric by adapting pulling actions to changing contact and tension conditions. Because large-scale real-world training…
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…
Progressive-Resolution Policy Distillation: Leveraging Coarse-Resolution Simulations for Time-Efficient Fine-Resolution Policy Learning
Yuki Kadokawa, Hirotaka Tahara, Takamitsu Matsubara
In earthwork and construction, excavators often encounter large rocks mixed with various soil conditions, requiring skilled operators. This paper presents a framework for achieving…