Yuki Kadokawa

According to our database, Yuki Kadokawa authored at least 13 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

DAPPER: Discriminability-Aware Policy-to-Policy Preference-Based Reinforcement Learning for Query-Efficient Robot Skill Acquisition.

Yuki Kadokawa, Jonas Frey, Takahiro Miki, Takamitsu Matsubara, Marco Hutter

IEEE Robotics Autom. Mag., March, 2026

ViSA: Visited-State Augmentation for Generalized Goal-Space Contrastive Reinforcement Learning.

Issa Nakamura, Tomoya Yamanokuchi, Yuki Kadokawa, Jia Qu, Shun Otsubo, Ken Miyamoto, Shotaro Miwa, Takamitsu Matsubara

CoRR, March, 2026

Robust Sim-to-Real Cloth Untangling through Reduced-Resolution Observations via Adaptive Force-Difference Quantization.

Yoshihisa Tsurumine, Yuki Kadokawa, Kohei Hayashi, Christian Diehm, Takamitsu Matsubara

CoRR, March, 2026

DeReCo: Decoupling Representation and Coordination Learning for Object-Adaptive Decentralized Multi-Robot Cooperative Transport.

Kazuki Shibata, Ryosuke Sota, Shandil Dhiresh Bosch, Yuki Kadokawa, Yoshihisa Tsurumine, Takamitsu Matsubara

CoRR, March, 2026

Prolonging Tool Life: Learning Skillful Use of General-Purpose Tools Through Lifespan-Guided Reinforcement Learning.

Po-Yen Wu, Cheng-Yu Kuo, Yuki Kadokawa, Takamitsu Matsubara

IEEE Access, 2026

Distilled Iterative Value Conversion: Reducing FPNN-to-SNN Conversion Errors via Distillation in Reinforcement Learning for Neurochip-Driven Edge Robots.

Yuki Kadokawa, Tomoya Yamanokuchi, Alonso Ramos Fernandez, Takanori Homma, Takamitsu Matsubara

IEEE Access, 2026

2025

Progressive-Resolution Policy Distillation: Leveraging Coarse-Resolution Simulations for Time-Efficient Fine-Resolution Policy Learning.

Yuki Kadokawa, Hirotaka Tahara, Takamitsu Matsubara

IEEE Trans Autom. Sci. Eng., 2025

Learning Quiet Walking for a Small Home Robot.

Ryo Watanabe, Takahiro Miki, Fan Shi, Yuki Kadokawa, Filip Bjelonic, Kento Kawaharazuka, Andrei Cramariuc, Marco Hutter

Proceedings of the IEEE International Conference on Robotics and Automation, 2025

2024

Robust iterative value conversion: Deep reinforcement learning for neurochip-driven edge robots.

Yuki Kadokawa, Tomohito Kodera, Yoshihisa Tsurumine, Shinya Nishimura, Takamitsu Matsubara

Robotics Auton. Syst., 2024

Progressive-Resolution Policy Distillation: Leveraging Coarse-Resolution Simulation for Time-Efficient Fine-Resolution Policy Learning.

Yuki Kadokawa, Hirotaka Tahara, Takamitsu Matsubara

CoRR, 2024

2023

Cyclic policy distillation: Sample-efficient sim-to-real reinforcement learning with domain randomization.

Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine, Takamitsu Matsubara

Robotics Auton. Syst., 2023

Learning Robotic Powder Weighing from Simulation for Laboratory Automation.

Yuki Kadokawa, Masashi Hamaya, Kazutoshi Tanaka

IROS, 2023

2021

Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA.

Yuki Kadokawa, Yoshihisa Tsurumine, Takamitsu Matsubara

IEEE Robotics Autom. Lett., 2021