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Norikazu Sugimoto
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2020 – today
- 2024
- [i2]Mitsuki Morita, Satoshi Yamamori, Satoshi Yagi, Norikazu Sugimoto, Jun Morimoto:
Goal-Conditioned Terminal Value Estimation for Real-time and Multi-task Model Predictive Control. CoRR abs/2410.04929 (2024) - 2023
- [j5]Sunhwi Kang, Koji Ishihara, Norikazu Sugimoto, Jun Morimoto:
Curriculum-based humanoid robot identification using large-scale human motion database. Frontiers Robotics AI 10 (2023)
2010 – 2019
- 2016
- [j4]Norikazu Sugimoto, Voot Tangkaratt, Thijs Wensveen, Tingting Zhao, Masashi Sugiyama
, Jun Morimoto:
Trial and Error: Using Previous Experiences as Simulation Models in Humanoid Motor Learning. IEEE Robotics Autom. Mag. 23(1): 96-105 (2016) - 2014
- [c11]Norikazu Sugimoto, Voot Tangkaratt, Thijs Wensveen, Tingting Zhao, Masashi Sugiyama
Efficient reuse of previous experiences in humanoid motor learning. Humanoids 2014: 554-559 - [i1]Norikazu Sugimoto, Voot Tangkaratt, Thijs Wensveen, Tingting Zhao, Masashi Sugiyama, Jun Morimoto:
Efficient Reuse of Previous Experiences to Improve Policies in Real Environment. CoRR abs/1405.2406 (2014) - 2013
- [c10]Norikazu Sugimoto, Jun Morimoto:
Trajectory-model-based reinforcement learning: Application to bimanual humanoid motor learning with a closed-chain constraint. Humanoids 2013: 429-434 - [c9]Karim Bouyarmane
BCI Control of Whole-Body Simulated Humanoid by Combining Motor Imagery Detection and Autonomous Motion Planning. ICONIP (1) 2013: 310-318 - [c8]Norikazu Sugimoto, Jun Morimoto:
Off-line path integral reinforcement learning using stochastic robot dynamics approximated by sparse pseudo-input Gaussian processes: Application to humanoid robot motor learning in the real environment. ICRA 2013: 1311-1316 - [c7]Rok Vuga, Matjaz Ogrinc, Andrej Gams
Motion capture and reinforcement learning of dynamically stable humanoid movement primitives. ICRA 2013: 5284-5290 - 2012
- [j3]Norikazu Sugimoto, Masahiko Haruno, Kenji Doya, Mitsuo Kawato:
MOSAIC for Multiple-Reward Environments. Neural Comput. 24(3): 577-606 (2012) - [j2]Norikazu Sugimoto, Jun Morimoto, Sang-Ho Hyon, Mitsuo Kawato:
The eMOSAIC model for humanoid robot control. Neural Networks 29: 8-19 (2012) - [c6]Tomoyuki Noda
Brain-controlled exoskeleton robot for BMI rehabilitation. Humanoids 2012: 21-27 - [c5]Ales Ude
Integrating surface-based hypotheses and manipulation for autonomous segmentation and learning of object representations. ICRA 2012: 1709-1715 - 2011
- [c4]Norikazu Sugimoto, Jun Morimoto:
Phase-dependent trajectory optimization for CPG-based biped walking using path integral reinforcement learning. Humanoids 2011: 255-260 - [c3]Norikazu Sugimoto, Jun Morimoto:
Switching multiple LQG controllers based on Bellman's optimality principle: Using full-state feedback to control a humanoid robot. IROS 2011: 3185-3191 - 2010
- [c2]Norikazu Sugimoto, Jun Morimoto, Sang-Ho Hyon, Mitsuo Kawato:
eMOSAIC Model for Humanoid Robot Control. SAB 2010: 447-457
2000 – 2009
- 2003
- [j1]Keiki Takadama, Yutaka L. Suematsu, Norikazu Sugimoto, Norberto Eiji Nawa, Katsunori Shimohara:
Cross-Element Validation in Multiagent-based Simulation: Switching Learning Mechanisms in Agents. J. Artif. Soc. Soc. Simul. 6(4) (2003) - [c1]Keiki Takadama, Yutaka L. Suematsu, Norikazu Sugimoto, Norberto Eiji Nawa, Katsunori Shimohara:
Towards Verification and Validation in Multiagent-Based Systems and Simulations: Analyzing Different Learning Bargaining Agents. MABS 2003: 26-42
Coauthor Index
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