Training an X-Arm 5 Robotic Arm with AMD Schola and Unreal Engine
This example provides a comprehensive walkthrough on how to setup all necessary pieces in order to perform training with the X-Arm 5 Robotic Arm.
Table of Contents
Setup and Training Tasks
Getting Started
Begin with the Setup guide to configure your Unreal Engine project and set up the X-ARM 5 robot. This includes:
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Initial Schola and Unreal Engine setup
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Importing the robot model using Datasmith
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Configuring physics meshes and constraints
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Creating target blocks and environment blueprints
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Setting up the world
Training Tasks
After completing the setup, there are three example training tasks:
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Task 1: Learn the fundamentals by training the agent to reach and pick a specific colored block from fixed positions. This task introduces the basic observation, action, and reward structures.
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Task 2: Build upon Task 1 by introducing randomized block positions. The agent must generalize its learned behavior to handle varying spatial configurations.
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Task 3: The most challenging task combines random target colors with random positions. This task also introduces advanced reward mechanisms based on progress tracking.
Prerequisites
Before starting, please refer to the ../../guides/setup_schola section to set up the Unreal Engine project and Schola plugin, if you haven’t already.