OpenSocInt: A Multi-modal Training Environment for Human-Aware Social Navigation

TL;DR

OpenSocInt is an open-source multi-modal simulation environment designed for training socially aware navigation agents, enabling exploration of perception, encoding, and agent behaviors in social contexts.

Contribution

It introduces a modular, open-source framework for social navigation training, facilitating multi-modal perception and interaction research.

Findings

Demonstrated the framework's capability through social navigation experiments

Enabled exploration of perceptual feature fusion in social contexts

Provided a publicly available tool for future research

Abstract

In this paper, we introduce OpenSocInt, an open-source software package providing a simulator for multi-modal social interactions and a modular architecture to train social agents. We described the software package and showcased its interest via an experimental protocol based on the task of social navigation. Our framework allows for exploring the use of different perceptual features, their encoding and fusion, as well as the use of different agents. The software is already publicly available under GPL at https://gitlab.inria.fr/robotlearn/OpenSocInt/.