Mind Your Manners! A Dataset and A Continual Learning Approach for Assessing Social Appropriateness of Robot Actions

07/24/2020
by   Jonas Tjomsland, et al.
1

To date, endowing robots with an ability to assess social appropriateness of their actions has not been possible. This has been mainly due to (i) the lack of relevant and labelled data, and (ii) the lack of formulations of this as a lifelong learning problem. In this paper, we address these two issues. We first introduce the Socially Appropriate Domestic Robot Actions dataset (MANNERS-DB), which contains appropriateness labels of robot actions annotated by humans. To be able to control but vary the configurations of the scenes and the social settings, MANNERS-DB has been created utilising a simulation environment by uniformly sampling relevant contextual attributes. Secondly, we train and evaluate a baseline Bayesian Neural Network (BNN) that estimates social appropriateness of actions in the MANNERS-DB. Finally, we formulate learning social appropriateness of actions as a continual learning problem using the uncertainty of the BNN parameters. The experimental results show that the social appropriateness of robot actions can be predicted with a satisfactory level of precision. Our work takes robots one step closer to a human-like understanding of (social) appropriateness of actions, with respect to the social context they operate in. To facilitate reproducibility and further progress in this area, the MANNERS-DB, the trained models and the relevant code will be made publicly available.

READ FULL TEXT

page 1

page 3

page 6

research
04/09/2023

CLVOS23: A Long Video Object Segmentation Dataset for Continual Learning

Continual learning in real-world scenarios is a major challenge. A gener...
research
06/30/2023

How Do Human Users Teach a Continual Learning Robot in Repeated Interactions?

Continual learning (CL) has emerged as an important avenue of research i...
research
03/03/2022

Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping through Continual Learning

While lifelong SLAM addresses the capability of a robot to adapt to chan...
research
07/09/2021

Behavior Self-Organization Supports Task Inference for Continual Robot Learning

Recent advances in robot learning have enabled robots to become increasi...
research
05/02/2020

Visually Grounded Continual Learning of Compositional Semantics

Children's language acquisition from the visual world is a real-world ex...
research
12/09/2021

Gradient-matching coresets for continual learning

We devise a coreset selection method based on the idea of gradient match...
research
01/14/2022

Decentralized Robot Learning for Personalization and Privacy

From learning assistance to companionship, social robots promise to enha...

Please sign up or login with your details

Forgot password? Click here to reset