Abstract
The increasing complexity of deep underwater tasks such as sample collection and maintenance of subsea infrastructure necessitates advanced technological solutions. Despite significant progress in underwater robotic grippers' design and operational capabilities, one pivotal area that requires further exploration is how to provide operators with a sense of the objects being handled. This research addresses the abovementioned challenge by presenting an innovative, low-cost approach to incorporate load cell technology into underwater grippers. It is focused on the integration of the load cell, the challenges of underwater force measurement, and the accuracy of the force readings obtained. The system is designed with the potential for future integratio n with a haptic feedback glove, although these aspects are not fully implemented in the current work. This paper presents the system architecture, load cell integration, calibration process, and performance evaluations in laboratory underwater conditions. Th e system is validated by measuring the gripping forces applied to various objects, including a steel rod, a cuboid, and a soft ball. The results demonstrate the feasibility and accuracy of force measurements in underwater manipulation tasks, laying the groundwork for future enhancements in underwater robotic control and operator feedback.
Original language | English |
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Pages (from-to) | 73-79 |
Number of pages | 7 |
Journal | IET Conference Proceedings |
Volume | 2024 |
Issue number | 11 |
DOIs | |
Publication status | Published - 3 Oct 2024 |
Event | Low-Cost Digital Solutions for Industrial Automation - Cambridge, United Kingdom Duration: 1 Oct 2024 → 2 Oct 2024 Conference number: 2 https://engage-events.ifm.eng.cam.ac.uk/Low-CostDigitalSolutionsforIndustrialAutomation |
Funding
This work is supported in part by the SeaSense for Sustainability research project from the UK Net Zero Technology Centre and the University of Strathclyde (Grant No. 1716541, 01/10/2022-31/01/2025). The authors would like to thank the robotics team members at the University of Strathclyde for their kind support, especially Dr. Quang Dan Le, Mr Mohamed Adlan, Ms Janjira Aphirakmethawong, Ms Meiling Jiang, Mr Mark Robertson, and Prof Xiutian Yan. The authors would like to acknowledge the use of ChatGPT for grammar revision in this document.
Keywords
- deep underwater tasks
- underwater gripper
- feedback glove
- haptic feedback