1 citations · 1 across the 6 of their papers we have counts for
7 papers
IK Seed Generator for Dual-Arm Human-like Physicality Robot with Mobile Base
Jun Takamatsu, Atsushi Kanehira, Kazuhiro Sasabuchi +2
Robots are strongly expected as a means of replacing human tasks. If a robot has a human-like physicality, the possibility of replacing human tasks increases. In the case of househ…
RL-Driven Data Generation for Robust Vision-Based Dexterous Grasping
Atsushi Kanehira, Naoki Wake, Kazuhiro Sasabuchi +2
This work presents reinforcement learning (RL)-driven data augmentation to improve the generalization of vision-action (VA) models for dexterous grasping. While real-to-sim-to-real…
A Taxonomy of Self-Handover
Naoki Wake, Atsushi Kanehira, Kazuhiro Sasabuchi +2
Self-handover, transferring an object between one's own hands, is a common but understudied bimanual action. While it facilitates seamless transitions in complex tasks, the strateg…
Plan-and-Act using Large Language Models for Interactive Agreement
Kazuhiro Sasabuchi, Naoki Wake, Atsushi Kanehira +2
Recent large language models (LLMs) are capable of planning robot actions. In this paper, we explore how LLMs can be used for planning actions with tasks involving situational huma…
Agreeing to Interact in Human-Robot Interaction using Large Language Models and Vision Language Models
Kazuhiro Sasabuchi, Naoki Wake, Atsushi Kanehira +2
In human-robot interaction (HRI), the beginning of an interaction is often complex. Whether the robot should communicate with the human is dependent on several situational factors…
VLM-driven Behavior Tree for Context-aware Task Planning
Naoki Wake, Atsushi Kanehira, Jun Takamatsu +2
The use of Large Language Models (LLMs) for generating Behavior Trees (BTs) has recently gained attention in the robotics community, yet remains in its early stages of development.…