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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | The University of Manchester |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Feb 29, 2028 |
| Duration | 1,247 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2932585 |
During nuclear decommissioning, operators face severe risks from unknown, hazardous and sharp objects like exposed wires. Accurate object recognition even in poorly lit and diverse environments is thus critical to improve safety. By enhancing robots with perception capabilities through visuo-haptic sensing, this project aims to significantly improve safety and efficiency in the decontamination processes.
To enable object recognition in challenging environments, the project will develop a visuo-haptic recognition system that combines tactile sensing with a wide range of vision sensors (including visible, infrared, and depth), aiming to enhance and improve the reliability of object recognition. To reduce recognition vagueness, active sensing methods will also be developed, enabling the robot to undertake optimal actions for exploration.
Furthermore, we will extract information from operators' manoeuvres, incorporating their insights of environmental assessments in robotic perception. This advanced perception capability is essential for robots to execute critical nuclear decommissioning tasks, such as dismantling, thereby contributing to more efficient, more reliable and safer operational procedures.
The University of Manchester
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