Multi-Robot Coordination and Layout Design for Automated Warehousing
Authors: Yulun Zhang, Matthew C. Fontaine, Varun Bhatt, Stefanos Nikolaidis, Jiaoyang Li
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we evaluate MAP-Elites and DSAGE and compare the optimized layouts with the human-designed ones. |
| Researcher Affiliation | Academia | Yulun Zhang1 , Matthew C. Fontaine2 , Varun Bhatt2 , Stefanos Nikolaidis2 and Jiaoyang Li1 1Robotics Institute, Carnegie Mellon University 2Department of Computer Science, University of Southern California |
| Pseudocode | No | The paper includes diagrams (Figure 3, Figure 8) illustrating the approach but does not present any formal pseudocode or algorithm blocks. |
| Open Source Code | Yes | We include the source code of the experiments in: https://github. com/lunjohnzhang/warehouse env gen public |
| Open Datasets | No | The paper describes self-generated layouts and scenarios for simulations, but does not provide specific access information (link, DOI, formal citation) to a publicly available or open dataset used for training, nor does it refer to established benchmark datasets. |
| Dataset Splits | No | The paper does not specify dataset splits (e.g., percentages, sample counts, or citations to predefined splits) for training, validation, or testing. |
| Hardware Specification | Yes | Our experiments are run on machines with Intel(R) Xeon(R) Gold 6248R CPU @ 3.00GHz, 251GB memory, and NVIDIA A100-SXM4-40GB GPU. |
| Software Dependencies | Yes | We use Python 3.9.7, PyTorch 1.13.1, and CUDA 11.7. |
| Experiment Setup | Yes | For both MAP-Elites and DSAGE, we set b = 50, Neval = 10, 000, T = 1, 000, and Ne = 5. ... We run the lifelong MAPF simulator on every human-designed or optimized layout that we evaluate in this section with Teval = 5, 000 timesteps for, unless explicitly stated otherwise, 10 times... |