研究者詳細 - 武田　一哉

論文 - 武田　一哉

分割表示 671 件中 1 - 20 件目／全件表示 >>

Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling

Fujii, K; Takeishi, N; Kawahara, Y; Takeda, K

NEURAL NETWORKS 171 巻頁： 40 - 52 2024年3月

L-DIG: A GAN-Based Method for LiDAR Point Cloud Processing under Snow Driving Conditions

Zhang, YX; Ding, M; Yang, HT; Niu, YJ; Feng, Y; Ohtani, K; Takeda, K

SENSORS 23 巻 ( 21 ) 2023年11月

Controllable Unsupervised Snow Synthesis by Latent Style Space Manipulation

Yang, HT; Carballo, A; Zhang, YX; Takeda, K

SENSORS 23 巻 ( 20 ) 2023年10月

Estimation of control area in badminton doubles with pose information from top and back view drone videos 査読有り

Ding Ning, Takeda Kazuya, Jin Wenhui, Bei Yingjiu, Fujii Keisuke

MULTIMEDIA TOOLS AND APPLICATIONS 2023年8月

Pitching strategy evaluation via stratified analysis using propensity score 査読有り

Nakahara Hiroshi, Takeda Kazuya, Fujii Keisuke

JOURNAL OF QUANTITATIVE ANALYSIS IN SPORTS 2023年5月

Localization System for Vehicle Navigation Based on GNSS/IMU Using Time-Series Optimization with Road Gradient Constrain

Takanose Aoki, Kondo Kaito, Hoda Yuta, Meguro Junichi, Takeda Kazuya

JOURNAL OF ROBOTICS AND MECHATRONICS 35 巻 ( 2 ) 頁： 387 - 397 2023年4月

Multi-Agent Deep-Learning Based Comparative Analysis of Team Sport Trajectories 査読有り

Zhang Ziyi, Bunker Rory, Takeda Kazuya, Fujii Keisuke

IEEE ACCESS 11 巻頁： 43305 - 43315 2023年

Expert-driven Rule-based Refinement of Semantic Segmentation Maps for Autonomous Vehicles

Manibardo Eric L., Lana Ibai, Del Ser Javier, Carballo Alexander, Takeda Kazuya

2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV 2023年

Synthesizing Realistic Snow Effects in Driving Images Using GANs and Real Data with Semantic Guidance

Yang Hanting, Ding Ming, Carballo Alexander, Zhang Yuxiao, Ohtani Kento, Niu Yinjie, Ge Maoning, Feng Yan, Takeda Kazuya

2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV 2023年

Open-world driving scene segmentation via multi-stage and multi-modality fusion of vision-language embedding 査読有り

Niu Yingjie, Ding Ming, Zhang Yuxiao, Ge Maoning, Yang Hanting, Takeda Kazuya

2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV 2023年

LiDAR Point Cloud Translation Between Snow and Clear Conditions Using Depth Images and GANs 査読有り

Zhang Yuxiao, Ding Ming, Yang Hanting, Niu Yingjie, Feng Yan, Ge Maoning, Carballo Alexander, Takeda Kazuya

2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV 2023年

Action Valuation of On- and Off-Ball Soccer Players Based on Multi-Agent Deep Reinforcement Learning

Nakahara, H; Tsutsui, K; Takeda, K; Fujii, K

IEEE ACCESS 11 巻頁： 131237 - 131244 2023年

Automatic Edge Error Judgment in Figure Skating Using 3D Pose Estimation from a Monocular Camera and IMUs

Tanaka, R; Suzuki, T; Takeda, K; Fujii, K

PROCEEDINGS OF THE 6TH INTERNATIONAL WORKSHOP ON MULTIMEDIA CONTENT ANALYSIS IN SPORTS, MMSPORTS 2023 頁： 41 - 48 2023年

Learning to Predict Navigational Patterns From Partial Observations 査読有り

Karlsson Robin, Carballo Alexander, Lepe-Salazar Francisco, Fujii Keisuke, Ohtani Kento, Takeda Kazuya

IEEE ROBOTICS AND AUTOMATION LETTERS 8 巻 ( 9 ) 頁： 5592 - 5599 2023年9月

Personalized lane changes using subjective risk-sensitive framework

Naren Bao, Alexander Carballo, Kazuya Takeda

Towards Human-Vehicle Harmonization 頁： 211 - 222 2023年3月

掲載種別：論文集(書籍)内論文

Most of the current researches on autonomous vehicles' control assume that all vehicles should have the same patterns of driving implemented, resulting in conservative or average systems. However, these results may not be acceptable to drivers who prefer a more aggressive style of driving, while extremely cautious drivers may consider the standard outputs to be too aggressive. In this chapter, we introduce risk-sensitive control (RSC), an inverse optimal control algorithm that estimates risk-sensitive driving features and incorporate them into a receding-horizon controller. RSC uses a meta-learning algorithm to update the parameters of the cost function, continuously improving the controller online as more and more driving data is gathered from the user for subjective risk feedback. The estimator takes into account the individual differences in subjective risk analysis, in terms of driving features and surrounding vehicle locations, by adjusting the cost function and constraints. We test this approach using five-lane change scenarios, some safe and some risky, with 30 real drivers in a CARLA simulation environment. Based on both quantitative and qualitative evaluations, our experimental results demonstrate that the proposed framework can generate users' preferred driving commands during lane changes, that is, commands associated with lower subjective risk, outperforming conventional, model-based predictive control methods in terms of replicating the user's own driving behavior.

DOI： 10.1515/9783110981223-016

Scopus

Framework for Generation and Removal of Multiple Types of Adverse Weather from Driving Scene Images 査読有り

Yang Hanting, Carballo Alexander, Zhang Yuxiao, Takeda Kazuya

SENSORS 23 巻 ( 3 ) 頁： 1548 2023年2月

Estimating the effect of hitting strategies in baseball using counterfactual virtual simulation with deep learning 査読有り

Hiroshi Nakahara, Kazuya Takeda, Keisuke Fujii

International Journal of Computer Science in Sport 22 巻 ( 1 ) 頁： 1 - 12 2023年1月

Perception and sensing for autonomous vehicles under adverse weather conditions: A survey 査読有り

Yuxiao Zhang, Alexander Carballo, Hanting Yang, Kazuya Takeda

ISPRS Journal of Photogrammetry and Remote Sensing 196 巻頁： 146 - 177 2023年1月

RSG-GCN: Predicting Semantic Relationships in Urban Traffic Scene With Map Geometric Prior

Tian Yafu, Carballo Alexander, Li Ruifeng, Takeda Kazuya

IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 4 巻頁： 244 - 260 2023年

Real-Time Graph-Based Optimization for GNSS-Doppler Integrated RTK-GNSS/IMU/DR Positioning System in Urban Area

Takanose Aoki, Takeuchi Eijiro, Carballo Alexander, Meguro Junichi, Takeda Kazuya

2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV 2023-June 巻 2023年

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論文 - 武田 一哉

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論文 - 武田　一哉