Zobrazeno 1 - 10
of 319
pro vyhledávání: '"Tsuji Toshiaki"'
Because imitation learning relies on human demonstrations in hard-to-simulate settings, the inclusion of force control in this method has resulted in a shortage of training data, even with a simple change in speed. Although the field of data augmenta
Externí odkaz:
http://arxiv.org/abs/2412.03252
Conventional methods of imitation learning for variable-speed motion have difficulty extrapolating speeds because they rely on learning models running at a constant sampling frequency. This study proposes variable-frequency imitation learning (VFIL),
Externí odkaz:
http://arxiv.org/abs/2411.12310
In recent years, imitation learning using neural networks has enabled robots to perform flexible tasks. However, since neural networks operate in a feedforward structure, they do not possess a mechanism to compensate for output errors. To address thi
Externí odkaz:
http://arxiv.org/abs/2411.12255
Autor:
Tsuji, Toshiaki
Recent advancements in imitation learning, particularly with the integration of LLM techniques, are set to significantly improve robots' dexterity and adaptability. This paper proposes using Mamba, a state-of-the-art architecture with potential appli
Externí odkaz:
http://arxiv.org/abs/2409.02636
Imitation learning enables robots to learn and replicate human behavior from training data. Recent advances in machine learning enable end-to-end learning approaches that directly process high-dimensional observation data, such as images. However, th
Externí odkaz:
http://arxiv.org/abs/2401.09691
Publikováno v:
IEEE RA-L, Vol. 9, No. 2, pp. 1198-1205, 2024
Object grasping is an important ability required for various robot tasks. In particular, tasks that require precise force adjustments during operation, such as grasping an unknown object or using a grasped tool, are difficult for humans to program in
Externí odkaz:
http://arxiv.org/abs/2311.09555
Autor:
Tsuji, Toshiaki, Kato, Yasuhiro
In contact-rich tasks, setting the stiffness of the control system is a critical factor in its performance. Although the setting range can be extended by making the stiffness matrix asymmetric, its stability has not been proven. This study focuses on
Externí odkaz:
http://arxiv.org/abs/2306.11983
Compliance control is an increasingly employed technique used in the robotic field. It is known that various mechanical properties can be reproduced depending on the design of the stiffness matrix, but the design theory that takes advantage of this h
Externí odkaz:
http://arxiv.org/abs/2210.16594
Robots are expected to replace menial tasks such as housework. Some of these tasks include nonprehensile manipulation performed without grasping objects. Nonprehensile manipulation is very difficult because it requires considering the dynamics of env
Externí odkaz:
http://arxiv.org/abs/2206.10289
Recently, motion generation by machine learning has been actively researched to automate various tasks. Imitation learning is one such method that learns motions from data collected in advance. However, executing long-term tasks remains challenging.
Externí odkaz:
http://arxiv.org/abs/2203.08619