4 papers
Bi-LAT: Bilateral Control-Based Imitation Learning via Natural Language and Action Chunking with Transformers
Takumi Kobayashi, Masato Kobayashi, Thanpimon Buamanee +1
We present Bi-LAT, a novel imitation learning framework that unifies bilateral control with natural language processing to achieve precise force modulation in robotic manipulation.…
MRHaD: Mixed Reality-based Hand-Drawn Map Editing Interface for Mobile Robot Navigation
Takumi Taki, Masato Kobayashi, Eduardo Iglesius +3
Mobile robot navigation systems are increasingly relied upon in dynamic and complex environments, yet they often struggle with map inaccuracies and the resulting inefficient path p…
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…
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…