A review of platforms for simulating embodied agents in 3D virtual environments

Abstract

The unprecedented rise in research interest in artificial intelligence (AI) and related areas, such as computer vision, machine learning, robotics, and cognitive science, during the last decade has fuelled the development of software platforms that can simulate embodied agents in 3D virtual environments. A simulator that closely mimics the physics of a real-world environment with embodied agents can allow open-ended experimentation, and can circumvent the need for real-world data collection, which is time-consuming, expensive, and in some cases, impossible without privacy invasion, thereby playing a significant role in progressing AI research. In this article, we review 22 simulation platforms reported in the literature. We classify them based on visual environment and physics. We present a comparison of these simulators based on their properties and functionalities from a user’s perspective. While no simulator is better than the others in all respects, a few stand out based on a rubric that encompasses the simulators’ properties, functionalities, availability and support. This review will guide users to choose the appropriate simulator for their application and provide a baseline to researchers for developing state-of-the-art simulators.

Publication Title

Artificial Intelligence Review

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