A Learning-from-Observation Framework: One-Shot Robot Teaching for Grasp-Manipulation-Release Household Operations

by   Naoki Wake, et al.

A household robot is expected to perform various manipulative operations with an understanding of the purpose of the task. To this end, robotic applications should provide an on-site robot teaching framework for non-experts. Here, we propose a Learning-from-Observation (LfO) framework for grasp-manipulation-release class household operations (GMR-operations). The framework maps human demonstrations to predefined task models through one-shot teaching. Each task model contains both high-level knowledge regarding the geometric constraints of tasks and low-level knowledge related to human postures. The key goal of this study is to design a task model that 1) covers various GMR-operations and 2) includes human postures to achieve tasks. We verify the applicability of our framework by testing the novel LfO system with a real robot. In addition, we quantify the coverage of the task model by analyzing online videos of household operations. Within the context of one-shot robot teaching, the contribution of this study is a framework that covers various GMR-operations and mimics human postures during operation.



There are no comments yet.


page 1

page 4


Task-oriented Motion Mapping on Robots of Various Configuration using Body Role Division

Many works in robot teaching either focus on teaching a high-level abstr...

A Mobile Manipulation System for One-Shot Teaching of Complex Tasks in Homes

We describe a mobile manipulation hardware and software system capable o...

Interactive Open-Ended Object, Affordance and Grasp Learning for Robotic Manipulation

Service robots are expected to autonomously and efficiently work in huma...

Quantifying Teaching Behaviour in Robot Learning from Demonstration

Learning from demonstration allows for rapid deployment of robot manipul...

Understanding Teacher Gaze Patterns for Robot Learning

Human gaze is known to be a strong indicator of underlying human intenti...

Semantic constraints to represent common sense required in household actions for multi-modal Learning-from-observation robot

The paradigm of learning-from-observation (LfO) enables a robot to learn...

Learning from Demonstration with Weakly Supervised Disentanglement

Robotic manipulation tasks, such as wiping with a soft sponge, require c...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.