activity
20242026
collaborators

9 papers

cs.RO2026

MRReP: Mixed Reality-based Hand-drawn Reference Path Editing Interface for Mobile Robot Navigation

Takumi Taki, Masato Kobayashi, Yuki Uranishi

Autonomous mobile robots operating in human-shared indoor environments often require paths that reflect human spatial intentions, such as avoiding interference with pedestrian flow…

cs.RO2026

Bi-HIL: Bilateral Control-Based Multimodal Hierarchical Imitation Learning via Subtask-Level Progress Rate and Keyframe Memory for Long-Horizon Contact-Rich Robotic Manipulation

Thanpimon Buamanee, Masato Kobayashi, Yuki Uranishi

Long-horizon contact-rich robotic manipulation remains challenging due to partial observability and unstable subtask transitions under contact uncertainty. While hierarchical archi…

cs.RO2026

MRPoS: Mixed Reality-Based Robot Navigation Interface Using Spatial Pointing and Speech with Large Language Model

Eduardo Iglesius, Masato Kobayashi, Yuki Uranishi

Recent advancements have made robot navigation more intuitive by transitioning from traditional 2D displays to spatially aware Mixed Reality (MR) systems. However, current MR inter…

cs.RO2025

Bi-VLA: Bilateral Control-Based Imitation Learning via Vision-Language Fusion for Action Generation

Masato Kobayashi, Thanpimon Buamanee

We propose Bilateral Control-Based Imitation Learning via Vision-Language Fusion for Action Generation (Bi-VLA), a novel framework that extends bilateral control-based imitation le…

cs.RO2025

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.…

cs.RO2025

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…