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.
@article{arxiv.2405.16818,
title = {Advancing Behavior Generation in Mobile Robotics through High-Fidelity Procedural Simulations},
author = {Victor A. Kich and Jair A. Bottega and Raul Steinmetz and Ricardo B. Grando and Ayanori Yorozu and Akihisa Ohya},
journal= {arXiv preprint arXiv:2405.16818},
year = {2024}
}
Comments
Preprint of 33rd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)