IPAB Seminar - 19/10/19

Title

Computer Vision and Machine Learning for Remote Infrastructure Inspections

Abstract

Abyss Solutions is a technology start-up that is on the cutting edge of infrastructure asset inspections. We design and operate custom data gathering robots and use machine learning and advanced data analytics to interpret the torrent of data that we collect.

Remote assets in the water and offshore industries have high inherent production, safety and operational risks due to the challenging operational and environmental conditions. Regular asset integrity inspections and maintenance procedures are in place to help reduce these risks and improve safety. However, such procedures are typically conducted by hand, making them expensive, sparse, prone to subjective biases and time consuming. For examples, divers are sent subsea to visually evaluate and report on degradation on support and operational structures. Furthermore, corrosion experts continuously walk through and examine the platforms to make timely decisions on managing accelerate degradation in the corrosive environment.

This talk presents an overview of advances and developments in computer vision and machine learning at Abyss Solutions, which are re-defining how inspections and assessment of such assets can be conducted in an accurate, comprehensive, cost effective and timely manner.

Bio

Suchet Bargoti has a background in field robotics, with a particular interest in enabling machines to perceive the world around and make autonomous data-driven decisions. Suchet’s background is in integrating machine learning and computer vision for robotics, developed through a PhD at the Australian Centre for Field Robotics (ACFR). His research has impacted many applications, such as agricultural robotics, urban automation, underwater mapping and space exploration. At Abyss Solutions he leads the technical vision of the rapidly growing business in automating condition assessments of remote offshore and subsea assets.