Integrating Foundation Models with Open RAN for Robots-Based Mobile Scenarios
Zhou, Longyu Feng, Wenjiao Li, Zonghang Leng, Supeng Guizani, Mohsen Quek, Tony Q.S.
Zhou, Longyu
Feng, Wenjiao
Li, Zonghang
Leng, Supeng
Guizani, Mohsen
Quek, Tony Q.S.
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Department
Machine Learning
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Journal article
Date
2025
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Language
English
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Abstract
The advancement of Artificial Intelligence (AI) has rendered robots an appealing paradigm for various applications, such as parcel sorting and handling in warehouse management. In this context, rapidly evolving mobile communication technology facilitates robot cooperation for efficient parcel sorting and handling. However, traditional AI solutions often struggle with unreasonable resource utilization, which makes it challenging to achieve both accurate parcel sorting and low-latency parcel handling. To address this issue, we propose a Foundation Model (FM)-empowered Open Radio Access Network (O-RAN) framework to achieve highly accurate and real-time robot cooperation in a pipeline manner. We first propose an adaptive FM splitting algorithm that decouples the sorting mission into multiple tasks to enable the robots to perform sequential task implementation for high-accuracy parcel sorting. Next, we present a cooperative path planning algorithm that allows a feasible number of robots to implement cooperative parcel handling with low latency and reduced energy consumption. Finally, we demonstrate the effectiveness of our proposed framework. The simulation results indicate that our solution achieves parcel sorting accuracy of up to 90% while reducing parcel handling latency by an average of 13.9% compared to traditional FM solutions.
Citation
L. Zhou, W. Feng, Z. Li, S. Leng, M. Guizani and T. Q. S. Quek, "Integrating Foundation Models with Open RAN for Robots-Based Mobile Scenarios," in IEEE Communications Magazine, vol. 63, no. 9, pp. 28-34, September 2025, doi: 10.1109/MCOM.001.2400729
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IEEE Communications Magazine
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Keywords
Intelligent Robots, Motion Planning, Robot Programming, Sorting, Foundation Models, Highly Accurate, Low Latency, Mobile Communication Technology, Mobile Scenarios, Network Frameworks, Radio Access Networks, Resources Utilizations, Robot Cooperation, Warehouse Management, Warehouses
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IEEE