Robotic Positioning for Quality Assurance of Feature-Sparse Components Using a Depth-Sensing Camera

Abstract

In this paper, a novel method for crawler positioning is presented utilizing an onboard depth-sensing camera which can operate in semi-structured, self-similar environments, using only measurements of the sample under inspection to navigate. Nondestructive evaluation at manufacture is a vital aspect of assuring the fitness for purpose of high-value marine assets, moreover, it is almost always a regulatory requirement to ensure build quality standards have been met. Traditionally these inspections were deployed manually by a trained operator in a laborious and timeconsuming manner. More recently, robotic crawler-based solutions have become available on the marketplace, however, these solutions are limited in their capabilities and still require significant manual intervention and set-up for each application. Additionally, GPS or prior knowledge of their surroundings which are critical to their operation are often unavailable in an active work environment. An autonomous, self-localizing system would provide significant benefits in these situations, but certain challenges arise from limited situational awareness and poor positional accuracy. The accuracy and robustness of the novel method were assessed and experimentally validated through ground truth readings from a Vicon motion capture system. The localization algorithm's ability to function on different materials and under various lighting conditions was also explored. Using the example of the receipt inspection of steel plate under 240 lux lighting, the system proved capable of positioning the crawler at the desired position within 5.7mm.

Using Phased Array Ultrasound to Localize Probes During the Inspection of Welds

“…Steps have been taken toward full autonomy through the development of localization systems capable of navigation through measurements of the inspection material being studied, achieving sub-10 -mm accuracy [16], [17]. A major benefit of this type of localization is that minimal assumptions are made during operation and their potential for implementation within a wide range of scenarios.…”