8 papers · 1 filter
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…
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.…
Modality-Driven Design for Multi-Step Dexterous Manipulation: Insights from Neuroscience
Naoki Wake, Atsushi Kanehira, Daichi Saito +4
Multi-step dexterous manipulation is a fundamental skill in household scenarios, yet remains an underexplored area in robotics. This paper proposes a modular approach, where each s…