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

arXiv 2405.16818 ↗First posted 27 May 2024cs.RO cs.HCcited by 1

On the map: Deep reinforcement learning methods → RL for robot locomotion and manipulation

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in RL for robot locomotion and manipulation, one of 15 directions in Deep reinforcement learning methods. Builds on 10 of its 31 references that are in the map. First posted on arXiv 27 May 2024.

Builds on

10 of 31 references.

References · 10

2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,191
2023ChatGPT for Robotics: Design Principles and Model Abilitiescited by 299
2022Robot Operating System 2: Design, Architecture, and Uses In The Wildcited by 199
2023SMART-LLM: Smart Multi-Agent Robot Task Planning using Large Language Modelscited by 153
2023Large Language Models for Robotics: A Surveycited by 133
2023Gen2Sim: Scaling up Robot Learning in Simulation with Generative Modelscited by 64
2023LLM as A Robotic Brain: Unifying Egocentric Memory and Controlcited by 33
2021Comparing Popular Simulation Environments in the Scope of Robotics and Reinforcement Learningcited by 12
2022Simulators for Mobile Social Robots:State-of-the-Art and Challengescited by 2
2022Jubileo: An Open-Source Robot and Framework for Research in Human-Robot Social Interactioncited by 1

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Citing papers per year: 2025: 1.

1 paper.

2025Reducing Latency in LLM-Based Natural Language Commands Processing for Robot Navigationcited by 1

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