Researcher Database

（Last updated : 2025-03-03 21:51:21）　

TANIGUCHI AKIRA

Department / Course College of Information Science and Engineering Department of Information Science and Engineering

Title / Position Lecturer

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Other Affiliations
1.	Graduate School of Information Science and Engineering

Academic background
1.	2018/03 Degree Acquisition	│ Ritsumeikan University Doctor of Engineering
2.	～2013/03	Department of Human and Computer Intelligence │ College of Information Science and Engineering │ Ritsumeikan University │ Graduated

Business career
1.	2022/04/01 ～	Lecturer │ College of Information Science and Engineering │ Ritsumeikan University
2.	2019/04/01 ～ 2022/03/31	Specially Appointed Assistant Professor │ College of Information Science and Engineering │ Ritsumeikan University
3.	2018/04/01 ～ 2019/03/31	Research Fellow (PD) │ │ Japan Society for the Promotionof Science
4.	2017/04/01 ～ 2018/03/31	Research Fellow (DC2) │ │ Japan Society for the Promotionof Science

Committee and society
1.	2021/05 ～	The section Robot Learning and Evolution in Frontiers in Robotics and AI Review Editor on the Editorial Board

Research activities
1.		The Institute of Systems, Control and Information Engineers
2.	2020/05/21 ～ 2022/05	∟ Editorial board
3.		THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS
4.		THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE
5.		THE ROBOTICS SOCIETY OF JAPAN

Subject of research
1.	Spatial Concept and Lexical Acquisition by Robot Based on Probabilistic Generative Models

Research summary
Spatial Concept and Lexical Acquisition by Robot Based on Probabilistic Generative Models In this research, we proposed a nonparametric Bayesian spatial concept acquisition method, SpCoA (A.Taniguchi et al., TCDS2016), that integrates the unsupervised generative model for self-localization and word segmentation in uttered sentences via latent variables related to spatial concepts. In addition, we developed an online learning algorithm, SpCoSLAM (A.Taniguchi et al., IROS2017), that can sequentially learn spatial concepts, a lexicon, and a map by integrating positions, speech signals, and scene images. The spatial concept represents a place category including the relationships between places and words. Lexical acquisition related to places is expected to enable a robot to improve its spatial cognition.

Present specialized field
Intelligent informatics, Intelligent robotics (Keyword：Symbol Emergence in Robotics, Intelligent Robotics, Artificial Intelligence, Machine Learning)

Papers
1.	2025/01/28	Data for Brain Reference Architecture of AF24Hippocampus-Amygdala │
2.	2024/12	ECRAP: Exophora Resolution and Classifying User Commands for Robot Action Planning by Large Language Models │ 2024 IEEE International Conference on Robotic Computing (IRC2024) │
3.	2024/12	Real-world Instance-specific Image Goal Navigation: Bridging Domain Gaps via Contrastive Learning │ 2024 IEEE International Conference on Robotic Computing (IRC2024) │
4.	2024/10	Object Instance Retrieval in Assistive Robotics: Leveraging Fine-Tuned SimSiam with Multi-View Images Based on 3D Semantic Map. │ IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2024), │
5.	2024/10	Pointing Frame Estimation with Audio-Visual Time Series Data for Daily Life Service Robots │ 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC) │
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Academic conference presentation
1.	2018	Active SLAM and Spatial Concepts Formation for a Mobile Robot in Home Environment
2.	2018	Spatial Concept Formation-based Semantic Mapping
3.	2017	Online Learning of Spatial Concepts and an Environmental Map by Integrating Nonparametric Bayesian Model and SLAM
4.	2017	Understanding of Places by Multimodal Spatial Concepts Learning Based on Coccurrence of Objects
5.	2015	Convolutional Neural Networkによる物体認識の自己位置推定への統計的活用

Works
1.	2024/01	Spatial cognition and semantic place understanding in mobile robots

Winning science prize
1.	2023/12	14th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023-Winter) Competitive Paper Award (Multi-agent Reinforcement Learning with Emergent Communication using Discrete and Indifferentiable Message)
2.	2023/11/10	13th IEEE International Conference on Development and Learning (ICDL) Best Conference Paper Finalist (Lexical Acquisition from Audio-Visual Streams using a Multimodal Recurrent State-Space Model)
3.	2018/05	The organization of the Whole Brain Architecture Initiative WBAI Encouragement Award
4.	2017/11	International Conference on Social Robotics (ICSR) Best Interactive Session (Finalist)
5.	2016/03	RoboCup Japan Open 2016 @Home Education League Third place, Finalist Award
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