Experimental Study on Behavior Acquisition of Mobile Robot by Deep Q-Network. - Hikaru Sasaki; Tadashi Horiuchi; Satoru Kato (J. Adv. Comput. Intell. Intell. Informatics, 2017)

Identification Method of Environmental Stiffness using Haptic Forceps for Brain Surgery. - Mika Aoki; Tomoyuki Shimono; Takuya Matsunaga; Takahiro Mizoguchi; Shunsuke Shibao; Hikaru Sasaki; Kouhei Ohnishi (AIM, 2018)

Multimodal Policy Search using Overlapping Mixtures of Sparse Gaussian Process Prior. - Hikaru Sasaki; Takamitsu Matsubara (ICRA, 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)

Exploiting Visual-Outer Shape for Tactile-Inner Shape Estimation of Objects Covered with Soft Materials. - Tomoya Miyamoto; Hikaru Sasaki; Takamitsu Matsubara (IEEE Robotics Autom. Lett., 2020)

Bayesian Policy Optimization for Waste Crane With Garbage Inhomogeneity. - Hikaru Sasaki; Terushi Hirabayashi; Kaoru Kawabata; Yukio Onuki; Takamitsu Matsubara (IEEE Robotics Autom. Lett., 2020)

Bayesian Disturbance Injection: Robust Imitation Learning of Flexible Policies. - Hanbit Oh; Hikaru Sasaki; Brendan Michael; Takamitsu Matsubara (ICRA, 2021)

Variational policy search using sparse Gaussian process priors for learning multimodal optimal actions. - Hikaru Sasaki; Takamitsu Matsubara (Neural Networks, 2021)

Gaussian Process Self-triggered Policy Search in Weakly Observable Environments. - Hikaru Sasaki; Terushi Hirabayashi; Kaoru Kawabata; Takamitsu Matsubara (ICRA, 2022)

Disturbance-injected Robust Imitation Learning with Task Achievement. - Hirotaka Tahara; Hikaru Sasaki; Hanbit Oh; Brendan Michael; Takamitsu Matsubara (ICRA, 2022)

Policy Optimization for Waste Crane Automation From Human Preferences. - Yuhwan Kwon; Hikaru Sasaki; Terushi Hirabayashi; Kaoru Kawabata; Takamitsu Matsubara (IEEE Access, 2023)

Bayesian Disturbance Injection: Robust imitation learning of flexible policies for robot manipulation. - Hanbit Oh; Hikaru Sasaki; Brendan Michael; Takamitsu Matsubara (Neural Networks, 2023)

Multi-step motion learning by combining learning-from-demonstration and policy-search. - Yaqiang Mo; Hikaru Sasaki; Takamitsu Matsubara; Kimitoshi Yamazaki (Adv. Robotics, 2023)

Disturbance Injection Under Partial Automation: Robust Imitation Learning for Long-Horizon Tasks. - Hirotaka Tahara; Hikaru Sasaki; Hanbit Oh; Edgar Anarossi; Takamitsu Matsubara (IEEE Robotics Autom. Lett., 2023)

Feasibility-aware Imitation Learning from Observations through a Hand-mounted Demonstration Interface. - Kei Takahashi; Hikaru Sasaki; Takamitsu Matsubara (CoRR, 2025)

Composite Gaussian processes flows for learning discontinuous multimodal policies. - Shu-yuan Wang; Hikaru Sasaki; Takamitsu Matsubara (Appl. Intell., 2025)

Robotic System for Chemical Experiment Automation with Dual Demonstration of End-effector and Jig Operations. - Hikaru Sasaki; Naoto Komeno; Takumi Hachimine; Kei Takahashi; Yu-ya Ohnishi; Tetsunori Sugawara; Araki Wakiuchi; Miho Hatanaka; Tomoyuki Miyao; Hiroharu Ajiro; Mikiya Fujii; Takamitsu Matsubara (CoRR, 2025)