1 citations · 1 across the 11 of their papers we have counts for
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ALPHA- 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
Masato Kobayashi, Thanpimon Buamanee, Takumi Kobayashi
Autonomous manipulation in everyday tasks requires flexible action generation to handle complex, diverse real-world environments, such as objects with varying hardness and softness…
DABI: Evaluation of Data Augmentation Methods Using Downsampling in Bilateral Control-Based Imitation Learning with Images
Masato Kobayashi, Thanpimon Buamanee, Yuki Uranishi
Autonomous robot manipulation is a complex and continuously evolving robotics field. This paper focuses on data augmentation methods in imitation learning. Imitation learning consi…
MRNaB: Mixed Reality-based Robot Navigation Interface using Optical-see-through MR-beacons
Eduardo Iglesius, Masato Kobayashi, Yuki Uranishi +1
Recent advancements in robotics have led to the development of numerous interfaces to enhance the intuitiveness of robot navigation. However, the reliance on traditional 2D display…
ILBiT: Imitation Learning for Robot Using Position and Torque Information based on Bilateral Control with Transformer
Masato Kobayashi, Thanpimon Buamanee, Yuki Uranishi +1
Autonomous manipulation in robot arms is a complex and evolving field of study in robotics. This paper introduces an innovative approach to this challenge by focusing on imitation…
Bi-ACT: Bilateral Control-Based Imitation Learning via Action Chunking with Transformer
Thanpimon Buamanee, Masato Kobayashi, Yuki Uranishi +1
Autonomous manipulation in robot arms is a complex and evolving field of study in robotics. This paper proposes work stands at the intersection of two innovative approaches in the…