95 citations · 136 across the 12 of their papers we have counts for
17 papers · 1 filter
Robotic Stroke Motion Following the Shape of the Human Back: Motion Generation and Psychological Effects
Akishige Yuguchi, Tomoki Ishikura, Sung-Gwi Cho +2
In this study, to perform the robotic stroke motions following the shape of the human back similar to the stroke motions by humans, in contrast to the conventional robotic stroke m…
GPT Models Meet Robotic Applications: Co-Speech Gesturing Chat System
Naoki Wake, Atsushi Kanehira, Kazuhiro Sasabuchi +2
This technical paper introduces a chatting robot system that utilizes recent advancements in large-scale language models (LLMs) such as GPT-3 and ChatGPT. The system is integrated…
Applying Learning-from-observation to household service robots: three common-sense formulation
Katsushi Ikeuchi, Jun Takamatsu, Kazuhiro Sasabuchi +2
Utilizing a robot in a new application requires the robot to be programmed at each time. To reduce such programmings efforts, we have been developing ``Learning-from-observation (L…
ChatGPT Empowered Long-Step Robot Control in Various Environments: A Case Application
Naoki Wake, Atsushi Kanehira, Kazuhiro Sasabuchi +2
This paper demonstrates how OpenAI's ChatGPT can be used in a few-shot setting to convert natural language instructions into a sequence of executable robot actions. The paper propo…
Task-sequencing Simulator: Integrated Machine Learning to Execution Simulation for Robot Manipulation
Kazuhiro Sasabuchi, Daichi Saito, Atsushi Kanehira +3
A task-sequencing simulator in robotics manipulation to integrate simulation-for-learning and simulation-for-execution is introduced. Unlike existing machine-learning simulation wh…
Interactive Task Encoding System for Learning-from-Observation
Naoki Wake, Atsushi Kanehira, Kazuhiro Sasabuchi +2
We present the Interactive Task Encoding System (ITES) for teaching robots to perform manipulative tasks. ITES is designed as an input system for the Learning-from-Observation (LfO…