Computer Graphics System for Reproducing Three-dimensional Shape from Idea Sketch. - Makoto Akeo; Hiroshi Hashimoto; Taisuke Kobayashi; Tetsuo Shibusawa (Comput. Graph. Forum, 1994)

Stability enhancement of 3-D biped walking based on Passive Dynamic Autonomous Control. - Tadayoshi Aoyama; Kosuke Sekiyama; Zhiguo Lu; Taisuke Kobayashi; Yasuhisa Hasegawa; Toshio Fukuda (Humanoids, 2012)

Locomotion selection of Multi-Locomotion Robot based on Falling Risk and moving efficiency. - Taisuke Kobayashi; Tadayoshi Aoyama; Kosuke Sekiyama; Zhiguo Lu; Yasuhisa Hasegawa; Toshio Fukuda (IROS, 2012)

Optimal control of energetically efficient ladder decent motion with internal stress adjustment using key joint method. - Zhiguo Lu; Kosuke Sekiyama; Tadayoshi Aoyama; Yasuhisa Hasegawa; Taisuke Kobayashi; Toshio Fukuda (IROS, 2012)

Stabilization and moving efficiency improvement by adjustment of moving speed in single locomotion. - Taisuke Kobayashi; Tadayoshi Aoyama; Kosuke Sekiyama; Toshio Fukuda (MHS, 2012)

Locomotion selection strategy for multi-locomotion robot based on stability and efficiency. - Taisuke Kobayashi; Tadayoshi Aoyama; Masafumi Sobajima; Kosuke Sekiyama; Toshio Fukuda (IROS, 2013)

Bipedal walking by humanoid robot with cane - Preventive usage of cane based on impulse force. - Taisuke Kobayashi; Tadayoshi Aoyama; Masafumi Sobajima; Kosuke Sekiyama; Toshio Fukuda (MHS, 2013)

Optimal selection of cane usage with humanoid robot. - Taisuke Kobayashi; Kosuke Sekiyama; Tadayoshi Aoyama; Yasuhisa Hasegawa; Toshio Fukuda (Humanoids, 2014)

Support of COG trajectory tracking by arm-swing with bipedal walking. - Taisuke Kobayashi; Kosuke Sekiyama; Tadayoshi Aoyama; Yasuhisa Hasegawa; Toshio Fukuda (MHS, 2014)

Optimal use of arm-swing for bipedal walking control. - Taisuke Kobayashi; Kosuke Sekiyama; Tadayoshi Aoyama; Yasuhisa Hasegawa; Toshio Fukuda (ICRA, 2015)

Dynamics-based virtual holonomic constraint for PDAC running. - Taisuke Kobayashi; Tadayoshi Aoyama; Yasuhisa Hasegawa; Kosuke Sekiyama; Toshio Fukuda (MHS, 2015)

Cane-supported walking by humanoid robot and falling-factor-based optimal cane usage selection. - Taisuke Kobayashi; Kosuke Sekiyama; Tadayoshi Aoyama; Toshio Fukuda (Robotics Auton. Syst., 2015)

Energetically Efficient Ladder Descent Motion With Internal Stress and Body Motion Optimized for a Multilocomotion Robot. - Zhiguo Lu; Kosuke Sekiyama; Tadayoshi Aoyama; Yasuhisa Hasegawa; Taisuke Kobayashi; Toshio Fukuda (IEEE Trans. Ind. Electron., 2015)

Selection Algorithm for Locomotion Based on the Evaluation of Falling Risk. - Taisuke Kobayashi; Tadayoshi Aoyama; Kosuke Sekiyama; Toshio Fukuda (IEEE Trans. Robotics, 2015)

Unified bipedal gait for walking and running by dynamics-based virtual holonomic constraint in PDAC. - Taisuke Kobayashi; Yasuhisa Hasegawa; Kosuke Sekiyama; Tadayoshi Aoyama; Toshio Fukuda (ICRA, 2016)

Quasi-passive dynamic autonomous control to enhance horizontal and turning gait speed control. - Taisuke Kobayashi; Kosuke Sekiyama; Yasuhisa Hasegawa; Tadayoshi Aoyama; Toshio Fukuda (IROS, 2016)

Modeling of the high-speed running humanoid robot. - Tomoro Ota; Kenichi Ohara; Akihiko Ichikawa; Taisuke Kobayashi; Yasuhisa Hasegawa; Toshio Fukuda (MHS, 2016)

Selection of two arm-swing strategies for bipedal walking to enhance both stability and efficiency. - Taisuke Kobayashi; Kosuke Sekiyama; Tadayoshi Aoyama; Yasuhisa Hasegawa; Toshio Fukuda (Adv. Robotics, 2016)

Biomechanical Energy Harvester with Continuously Variable Transmission: Prototyping and Preliminary Evaluation. - Yutaro Ikawa; Taisuke Kobayashi; Takamitsu Matsubara (AIM, 2018)

Check Regularization: Combining Modularity and Elasticity for Memory Consolidation. - Taisuke Kobayashi (ICANN (2), 2018)

Practical Fractional-Order Neuron Dynamics for Reservoir Computing. - Taisuke Kobayashi (ICANN (3), 2018)

Bottom-up Multi-agent Reinforcement Learning for Selective Cooperation. - Takumi Aotani; Taisuke Kobayashi; Kenji Sugimoto (SMC, 2018)

Unified bipedal gait for autonomous transition between walking and running in pursuit of energy minimization. - Taisuke Kobayashi; Kosuke Sekiyama; Yasuhisa Hasegawa; Tadayoshi Aoyama; Toshio Fukuda (Robotics Auton. Syst., 2018)

Multi-Contacts Force-Reactive Walking Control during Physical Human-Humanoid Interaction. - Taisuke Kobayashi; Emmanuel C. Dean-Leon; Julio Rogelio Guadarrama-Olvera; Florian Bergner; Gordon Cheng (Humanoids, 2019)

Variational Deep Embedding with Regularized Student-t Mixture Model. - Taisuke Kobayashi (ICANN (3), 2019)

Continual Learning Exploiting Structure of Fractal Reservoir Computing. - Taisuke Kobayashi; Toshiki Sugino (ICANN (Workshop), 2019)

Reward-Punishment Actor-Critic Algorithm Applying to Robotic Non-grasping Manipulation. - Taisuke Kobayashi; Takumi Aotani; Julio Rogelio Guadarrama-Olvera; Emmanuel C. Dean-Leon; Gordon Cheng (ICDL-EPIROB, 2019)

Impedance Control based Assistive Mobility Aid through Online Classification of User's State. - Shunki Itadera; Taisuke Kobayashi; Jun Nakanishi; Tadayoshi Aoyama; Yasuhisa Hasegawa (SII, 2019)

Student-t policy in reinforcement learning to acquire global optimum of robot control. - Taisuke Kobayashi (Appl. Intell., 2019)

TAdam: A Robust Stochastic Gradient Optimizer. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (CoRR, 2020)

Deep unfolding-based output feedback control design for linear systems with input saturation. - Koki Kobayashi; Masaki Ogura 001; Taisuke Kobayashi; Kenji Sugimoto (CoRR, 2020)

Reinforcement learning for quadrupedal locomotion with design of continual-hierarchical curriculum. - Taisuke Kobayashi; Toshiki Sugino (Eng. Appl. Artif. Intell., 2020)

q-VAE for Disentangled Representation Learning and Latent Dynamical Systems. - Taisuke Kobayashi (IEEE Robotics Autom. Lett., 2020)

Adaptive Eligibility Traces for Online Deep Reinforcement Learning. - Taisuke Kobayashi (IAS, 2021)

Proximal Policy Optimization with Relative Pearson Divergence. - Taisuke Kobayashi (ICRA, 2021)

Adaptive t-Momentum-based Optimization for Unknown Ratio of Outliers in Amateur Data in Imitation Learning. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (IROS, 2021)

Behavioral Cloning from Observation with Bi-directional Dynamics Model. - Tobias Betz; Hidehito Fujiishi; Taisuke Kobayashi (SII, 2021)

Towards Deep Robot Learning with Optimizer applicable to Non-stationary Problems. - Taisuke Kobayashi (SII, 2021)

Meta-Optimization of Bias-Variance Trade-Off in Stochastic Model Learning. - Takumi Aotani; Taisuke Kobayashi; Kenji Sugimoto (IEEE Access, 2021)

Bottom-up multi-agent reinforcement learning by reward shaping for cooperative-competitive tasks. - Takumi Aotani; Taisuke Kobayashi; Kenji Sugimoto (Appl. Intell., 2021)

Safe and efficient imitation learning by clarification of experienced latent space. - Hidehito Fujiishi; Taisuke Kobayashi; Kenji Sugimoto (Adv. Robotics, 2021)

Towards physical interaction-based sequential mobility assistance using latent generative model of movement state. - Shunki Itadera; Taisuke Kobayashi; Jun Nakanishi; Tadayoshi Aoyama; Yasuhisa Hasegawa (Adv. Robotics, 2021)

Mirror-Descent Inverse Kinematics for Box-constrained Joint Space. - Taisuke Kobayashi (CoRR, 2021)

Optimization Algorithm for Feedback and Feedforward Policies towards Robot Control Robust to Sensing Failures. - Taisuke Kobayashi; Kenta Yoshizawa (CoRR, 2021)

Hyperbolically-Discounted Reinforcement Learning on Reward-Punishment Framework. - Taisuke Kobayashi (CoRR, 2021)

Towards Autonomous Driving of Personal Mobility with Small and Noisy Dataset using Tsallis-statistics-based Behavioral Cloning. - Taisuke Kobayashi; Takahito Enomoto (CoRR, 2021)

t-soft update of target network for deep reinforcement learning. - Taisuke Kobayashi; Wendyam Eric Lionel Ilboudo (Neural Networks, 2021)

Hexapod locomotion with CPG. - Taisuke Kobayashi (IEEE DataPort, 2021)

L2C2: Locally Lipschitz Continuous Constraint towards Stable and Smooth Reinforcement Learning. - Taisuke Kobayashi (IROS, 2022)

Whole-Body Multicontact Haptic Human-Humanoid Interaction Based on Leader-Follower Switching: A Robot Dance of the "Box Step". - Taisuke Kobayashi; Emmanuel C. Dean-Leon; Julio Rogelio Guadarrama-Olvera; Florian Bergner; Gordon Cheng (Adv. Intell. Syst., 2022)

AdaTerm: Adaptive T-Distribution Estimated Robust Moments towards Noise-Robust Stochastic Gradient Optimizer. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (CoRR, 2022)

Proximal Policy Optimization with Adaptive Threshold for Symmetric Relative Density Ratio. - Taisuke Kobayashi (CoRR, 2022)

Real-time Sampling-based Model Predictive Control based on Reverse Kullback-Leibler Divergence and Its Adaptive Acceleration. - Taisuke Kobayashi; Kota Fukumoto (CoRR, 2022)

Reward Bonuses with Gain Scheduling Inspired by Iterative Deepening Search. - Taisuke Kobayashi (CoRR, 2022)

Sample-efficient gear-ratio optimization for biomechanical energy harvester. - Taisuke Kobayashi; Yutaro Ikawa; Takamitsu Matsubara (Int. J. Intell. Robotics Appl., 2022)

Light-weight behavior-based continuous authentication for personalized mobile robot. - Taisuke Kobayashi; Toshiya Mabuchi; Mato Kosaka (Int. J. Intell. Robotics Appl., 2022)

Optimistic reinforcement learning by forward Kullback-Leibler divergence optimization. - Taisuke Kobayashi (Neural Networks, 2022)

Adaptive and multiple time-scale eligibility traces for online deep reinforcement learning. - Taisuke Kobayashi (Robotics Auton. Syst., 2022)

Latent Representation in Human-Robot Interaction With Explicit Consideration of Periodic Dynamics. - Taisuke Kobayashi; Shingo Murata; Tetsunari Inamura (IEEE Trans. Hum. Mach. Syst., 2022)

Robust Stochastic Gradient Descent With Student-t Distribution Based First-Order Momentum. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Kenji Sugimoto (IEEE Trans. Neural Networks Learn. Syst., 2022)

Domains as Objectives: Multi-Domain Reinforcement Learning with Convex-Coverage Set Learning for Domain Uncertainty Awareness. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Takamitsu Matsubara (IROS, 2023)

Soft Actor-Critic Algorithm with Truly Inequality Constraint. - Taisuke Kobayashi (CoRR, 2023)

Intentionally-underestimated Value Function at Terminal State for Temporal-difference Learning with Mis-designed Reward. - Taisuke Kobayashi (CoRR, 2023)

Design of restricted normalizing flow towards arbitrary stochastic policy with computational efficiency. - Taisuke Kobayashi; Takumi Aotani (Adv. Robotics, 2023)

Sparse representation learning with modified q-VAE towards minimal realization of world model. - Taisuke Kobayashi; Ryoma Watanuki (Adv. Robotics, 2023)

AdaTerm: Adaptive T-distribution estimated robust moments for Noise-Robust stochastic gradient optimization. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Takamitsu Matsubara (Neurocomputing, 2023)

Real-time Detailed Self-collision Avoidance in Whole-body Model Predictive Control. - Takanori Jin; Taisuke Kobayashi; Masahiro Doi (Humanoids, 2024)

Consolidated Adaptive T-soft Update for Deep Reinforcement Learning. - Taisuke Kobayashi (IJCNN, 2024)

Cooperative Transport by Manipulators with Uncertainty-Aware Model-Based Reinforcement Learning. - Takumi Aotani; Taisuke Kobayashi (SII, 2024)

Autonomous Driving of Personal Mobility by Imitation Learning from Small and Noisy Dataset. - Taisuke Kobayashi; Takahito Enomoto (SII, 2024)

Autonomous Driving from Diverse Demonstrations with Implicit Selection of Optimal Mode. - Taisuke Kobayashi; Yusuke Takeda (SII, 2024)

Domains as Objectives: Domain-Uncertainty-Aware Policy Optimization through Explicit Multi-Domain Convex Coverage Set Learning. - Wendyam Eric Lionel Ilboudo; Taisuke Kobayashi; Takamitsu Matsubara (CoRR, 2024)

DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning. - Taisuke Kobayashi (CoRR, 2024)

Weber-Fechner Law in Temporal Difference learning derived from Control as Inference. - Keiichiro Takahashi; Taisuke Kobayashi; Tomoya Yamanokuchi; Takamitsu Matsubara (CoRR, 2024)

Real-Time Spatiotemporal Assistance for Micromanipulation Using Imitation Learning. - Ryoya Mori; Tadayoshi Aoyama; Taisuke Kobayashi; Kazuya Sakamoto; Masaru Takeuchi; Yasuhisa Hasegawa (IEEE Robotics Autom. Lett., 2024)

Latent regression based model predictive control for tissue triangulation. - Songtao Liu; Jacinto Colan; Yaonan Zhu; Taisuke Kobayashi; Kazunari Misawa; Masaru Takeuchi; Yasuhisa Hasegawa (Adv. Robotics, 2024)

Constrained footstep planning using model-based reinforcement learning in virtual constraint-based walking. - Takanori Jin; Taisuke Kobayashi; Takamitsu Matsubara (Adv. Robotics, 2024)

Revisiting experience replayable conditions. - Taisuke Kobayashi (Appl. Intell., 2024)

Adaptive Absolute-Relative Rating for Noise Rejection in Behavioral Cloning based on Tsallis Statistics. - Taisuke Kobayashi; Tadayoshi Aoyama (SII, 2025)

Extraction of Latent Variables for Modeling Subjective Quality in Time-series Human-Robot Interaction. - Yoshiaki Mizuchi; Taisuke Kobayashi; Tetsunari Inamura (SII, 2025)

LiRA: Light-Robust Adversary for model-based reinforcement learning in real world. - Taisuke Kobayashi (Robotics Auton. Syst., 2025)

Improvements of Dark Experience Replay and Reservoir Sampling towards Better Balance between Consolidation and Plasticity. - Taisuke Kobayashi (CoRR, 2025)

CubeDAgger: Improved Robustness of Interactive Imitation Learning without Violation of Dynamic Stability. - Taisuke Kobayashi (CoRR, 2025)

Variational Adaptive Noise and Dropout towards Stable Recurrent Neural Networks. - Taisuke Kobayashi; Shingo Murata (CoRR, 2025)

Skin-Machine Interface with Multimodal Contact Motion Classifier. - Alberto Confente; Takanori Jin; Taisuke Kobayashi; Julio Rogelio Guadarrama-Olvera; Gordon Cheng (CoRR, 2025)