Deep dynamic policy programming for robot control with raw images. - Yoshihisa Tsurumine; Yunduan Cui; Eiji Uchibe; Takamitsu Matsubara (IROS, 2017)

Learning Deep Dynamical Models of a Waste Incineration Plant from In-furnace Images and Process Data. - Takumi Kaneko; Yoshihisa Tsurumine; James Poon; Yukio Onuki; Yingda Dai; Kaoru Kawabata; Takamitsu Matsubara (CASE, 2019)

Generative Adversarial Imitation Learning with Deep P-Network for Robotic Cloth Manipulation. - Yoshihisa Tsurumine; Yunduan Cui; Kimitoshi Yamazaki; Takamitsu Matsubara (Humanoids, 2019)

Deep reinforcement learning with smooth policy update: Application to robotic cloth manipulation. - Yoshihisa Tsurumine; Yunduan Cui; Eiji Uchibe; Takamitsu Matsubara (Robotics Auton. Syst., 2019)

Combining Model Predictive Path Integral with Kalman Variational Auto-encoder for Robot Control from Raw Images. - Yuhwan Kwon; Takumi Kaneko; Yoshihisa Tsurumine; Hikaru Sasaki; Kimiko Motonaka; Seiji Miyoshi; Takamitsu Matsubara (SII, 2020)

Learning Food-arrangement Policies from Raw Images with Generative Adversarial Imitation Learning. - Junki Matsuoka; Yoshihisa Tsurumine; Yuhwan Kwon; Takamitsu Matsubara; Takeshi Shimmura; Sadao Kawamura (UR, 2020)

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)

Variationally Autoencoded Dynamic Policy Programming for Robotic Cloth Manipulation Planning based on Raw Images. - Yoshihisa Tsurumine; Takamitsu Matsubara (SII, 2022)

Physically Consistent Preferential Bayesian Optimization for Food Arrangement. - Yuhwan Kwon; Yoshihisa Tsurumine; Takeshi Shimmura; Sadao Kawamura; Takamitsu Matsubara (IEEE Robotics Autom. Lett., 2022)

Randomized-to-Canonical Model Predictive Control for Real-World Visual Robotic Manipulation. - Tomoya Yamanokuchi; Yuhwan Kwon; Yoshihisa Tsurumine; Eiji Uchibe; Jun Morimoto; Takamitsu Matsubara (IEEE Robotics Autom. Lett., 2022)

Goal-aware generative adversarial imitation learning from imperfect demonstration for robotic cloth manipulation. - Yoshihisa Tsurumine; Takamitsu Matsubara (Robotics Auton. Syst., 2022)

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)

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)

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation. - Ing-Sheng Bernard-Tiong; Yoshihisa Tsurumine; Ryosuke Sota; Kazuki Shibata; Takamitsu Matsubara (SII, 2025)

Diffusion Model and RRT*-Based Methods for Reflected Mass Optimization in Motion Planning. - David Gutierrez-Moreno; Simon Armleder; Yuhwan Kwon; Takumi Hachimine; Yoshihisa Tsurumine; Takamitsu Matsubara; Gordon Cheng (SII, 2025)

Self-Supervised Learning of Grasping Arbitrary Objects On-the-Move. - Takuya Kiyokawa; Eiki Nagata; Yoshihisa Tsurumine; Yuhwan Kwon; Takamitsu Matsubara (SII, 2025)