Mitigating RGB-D camera errors for robust ultrasonic inspections using a force-torque sensor
Source abstract
Abstract
Robot-based phased array ultrasonic testing is widely used for precise defect detection, particularly in complex geometries and various materials. Compact robots with miniature arms can inspect constrained areas, but payload limitations restrict sensor choice. RGB-D cameras, due to their small size and light weight, capture RGB colour and depth data, creating colourised 3D point clouds for scene representation. These point clouds help estimate surface normals to align the ultrasound transducer on complex surfaces. However, sole reliance on RGB-D cameras can lead to inaccuracies, affecting ultrasonic beam direction and test results. This paper investigates the impact of transducer pose and RGB-D camera limitations on ultrasonic inspections and proposes a novel method using force-torque sensors to mitigate errors from inaccurately estimated normals from the camera. The force-torque sensor, integrated into the robot end effector, provides tactile feedback to the controller, enabling joint angle adjustments to correct errors in the estimated normal. Experimental results show the successful application of ultrasound transducers using this method, even with significant misalignment. Adjustments took approximately 4 seconds to correct deviations from 12.55°, with an additional 4 seconds to ensure the probe was parallel to the surface, enhancing ultrasonic inspection accuracy in complex, constrained environments.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Soft Robotics and Applications · Robot Manipulation and Learning · Robotics and Sensor-Based Localization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Ulster University
University of Strathclyde
Funding
EPSRC “Delivering Enhanced Through-Life Nuclear Asset Management”
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