Advancing Behavior Generation in Mobile Robotics through High-Fidelity Procedural Simulations

TL;DR

YamaS is a high-fidelity simulator combining Unity3D and ROS, supporting advanced robot navigation research, procedural environments, and VR integration for enhanced AI and HRI development.

Contribution

The paper introduces YamaS, a versatile simulator with procedural generation, high-fidelity sensor simulation, and VR support, advancing research in robot navigation and AI training.

Findings

High accuracy in sensor simulation compared to real robots

Supports multi-agent and procedural environment generation

Enables immersive HRI studies with VR integration

Abstract

This paper introduces YamaS, a simulator integrating Unity3D Engine with Robotic Operating System for robot navigation research and aims to facilitate the development of both Deep Reinforcement Learning (Deep-RL) and Natural Language Processing (NLP). It supports single and multi-agent configurations with features like procedural environment generation, RGB vision, and dynamic obstacle navigation. Unique to YamaS is its ability to construct single and multi-agent environments, as well as generating agent's behaviour through textual descriptions. The simulator's fidelity is underscored by comparisons with the real-world Yamabiko Beego robot, demonstrating high accuracy in sensor simulations and spatial reasoning. Moreover, YamaS integrates Virtual Reality (VR) to augment Human-Robot Interaction (HRI) studies, providing an immersive platform for developers and researchers. This fusion establishes YamaS as a versatile and valuable tool for the development and testing of autonomous systems, contributing to the fields of robot simulation and AI-driven training methodologies.