Motion Generation Using Bilateral Control-Based Imitation Learning with Autoregressive Learning
Saitama University（埼玉大学）；University of Tsukuba（筑波大学）
Ayumu Sasagawa, Sho Sakaino, Toshiaki Tsuji
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Robots that can execute various tasks automatically on behalf of humans are becoming an increasingly important focus of research in the field of robotics. Imitation learning has been studied as an efficient and high-performance method, and imitation learning based on bilateral control has been proposed as a method that can realize fast motion. However, because this method cannot implement autoregressive learning, this method may not generate desirable long-term behavior. Therefore, in this paper, we propose a method of autoregressive learning for bilateral control-based imitation learning. A new neural network model for implementing autoregressive learning is proposed. In this study, three types of experiments are conducted to verify the effectiveness of the proposed method. The performance is improved compared to conventional approaches; the proposed method has the highest rate of success. Owing to the structure and autoregressive learning of the proposed model, the proposed method can generate the desirable motion for successful tasks and have a high generalization ability for environmental changes.
Bi-VLA: Bilateral Control-Based Imitation Learning via Vision-Language Fusion for Action Generation
D3 Center, The University of Osaka（大阪大学D3中心）；Graduate School of Information Science and Technology, The University of Osaka（大阪大学信息科学与技术研究生院）；Graduate School of Maritime Sciences, Kobe University（兵库大学海运研究生院）
Bi-LAT: Bilateral Control-Based Imitation Learning via Natural Language and Action Chunking with Transformers
Graduate School of Information Science and Technology, The University of Osaka（信息科学与技术研究生学校，大阪大学）；D3 Center, The University of Osaka（大阪大学D3中心）；Graduate School of Maritime Sciences, Kobe University（海洋科学研究生学校， Kobe大学）
Design and Experimental Validation of Sensorless 4-Channel Bilateral Teleoperation for Low-Cost Manipulators
Degree Programs in Intelligent and Mechanical Interaction Systems, University of Tsukuba（智能与机械交互系统专业，东京大学）；Faculty of Engineering, Information and Systems, University of Tsukuba（工程、信息与系统学部，东京大学）；Department of Electrical Engineering, Electronics, and Applied Physics, Saitama University（电子工程、电子学与应用物理系，埼玉大学）
Input-gated Bilateral Teleoperation: An Easy-to-implement Force Feedback Teleoperation Method for Low-cost Hardware
Research & Development Group, Hitachi, Ltd.（日立株式会社研发部）；Department of Intermedia Art and Science School of Fundamental Science and Engineering, Waseda University（早稻田大学基础科学与工程学部多媒体艺术与科学系）
Variable-Speed Teaching-Playback as Real-World Data Augmentation for Imitation Learning
Master’s Program in Intelligent and Mechanical Interaction Systems, Degree Programs in Systems and Information and Engineering, Graduate School of Science and Technology, University of Tsukuba, Japan（茨川大学科学技术研究生院系统与信息工程学系智能与机械交互系统硕士课程）；Doctoral Program in Intelligent and Mechanical Interaction Systems, Degree Programs in Systems and Information and Engineering, Graduate School of Science and Technology, University of Tsukuba, Japan（茨川大学科学技术研究生院系统与信息工程学系智能与机械交互系统博士课程）；Department of Intelligent Interaction Technologies, Institute of Systems and Information Engineering, University of Tsukuba, Japan（茨川大学系统与信息工程研究所智能交互技术系）；Graduate School of Science and Engineering, Saitama University, Saitama, Japan（埼玉大学工学研究科）
ALPHA-$α$ and Bi-ACT Are All You Need: Importance of Position and Force Information/Control for Imitation Learning of Unimanual and Bimanual Robotic Manipulation with Low-Cost System
Osaka University（大阪大学）；Graduate School of Information Science and Technology of Osaka University（大阪大学信息科学与技术研究生院）；School of Engineering Science, Osaka University（大阪大学工程科学学院）
