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Official Code Repository for "Optimal Robotic Assembly Sequence Planning: A Sequential Decision-Making Approach"

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Optimal Robotic Assembly Sequence Planning Code

License: MIT

Code for the paper: "Optimal Robotic Assembly Sequence Planning: A Sequential Decision-Making Approach"

Installation

You can recreate the python environment used to run these files via:

conda create --name <env> --file requirements.txt

Similiarily, using a standard Python 3 installation, you can also use:

python3 -m venv env
source env/bin/activate
pip install -r pipRequirements.txt

Running the Code

A few example scenarios are provided inside the Python Juypter Notebooks under the "Scenario Initialization" sections. The GEAP file is for the Graph-Exploration Assembly Planners (GEAPs) discussed in our "Methods" section, and the DQN file holds the Learning-Based methods.

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