  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.
