VisualEnv: visual Gym environments with Blender
Andrea Scorsoglio, Roberto Furfaro

TL;DR
VisualEnv is a novel tool that combines Blender and OpenAI Gym to create customizable, photorealistic visual environments for reinforcement learning research, enabling more realistic training scenarios.
Contribution
It introduces an integrated framework that leverages Blender's rendering capabilities within Gym for customizable, photorealistic environments in reinforcement learning.
Findings
Successfully created diverse visual environments for RL agents.
Demonstrated improved realism in training scenarios.
Showcased flexibility and ease of environment customization.
Abstract
In this paper VisualEnv, a new tool for creating visual environment for reinforcement learning is introduced. It is the product of an integration of an open-source modelling and rendering software, Blender, and a python module used to generate environment model for simulation, OpenAI Gym. VisualEnv allows the user to create custom environments with photorealistic rendering capabilities and full integration with python. The framework is described and tested on a series of example problems that showcase its features for training reinforcement learning agents.
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Taxonomy
TopicsReinforcement Learning in Robotics · Simulation Techniques and Applications
MethodsRoIPool · RoIAlign · Softmax
