Teleoperated Omni-directional Dual Arm Mobile Manipulation Robotic System with Shared Control for Retail Store
Abstract
The swiftly expanding retail sector is increasingly adopting autonomous mobile robots empowered by artificial intelligence and machine learning algorithms to gain an edge in the competitive market. However, these autonomous robots encounter challenges in adapting to the dynamic nature of retail products, often struggling to operate autonomously in novel situations. In this study, we introduce an omni-directional dual-arm mobile robot specifically tailored for use in retail environments. Additionally, we propose a tele-operation method that enables shared control between the robot and a human operator. This approach utilizes a Virtual Reality (VR) motion capture system to capture the operator's commands, which are then transmitted to the robot located remotely in a retail setting. Furthermore, the robot is equipped with heterogeneous grippers on both manipulators, facilitating the handling of a wide range of items. We validate the efficacy of the proposed system through testing in a mockup of retail environment, demonstrating its ability to manipulate various commonly encountered retail items using both single and dual-arm coordinated manipulation techniques.
Cite
@article{arxiv.2602.23923,
title = {Teleoperated Omni-directional Dual Arm Mobile Manipulation Robotic System with Shared Control for Retail Store},
author = {Rolif Lima and Somdeb Saha and Nijil George and Vismay Vakharia and Shubham Parab and Sahil Gaonkar and Vighnesh Vatsal and Kaushik Das},
journal= {arXiv preprint arXiv:2602.23923},
year = {2026}
}
Comments
This work has been accepted for publication in the Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC 2024). $\copyright$ IEEE. The final version is available via IEEE Xplore