OCRAIM
Bridging Innovation and Reality: Transforming Asset Inspection with Robotics for a Safer, Sustainable Future
This workshop aims to bridge the gap between cutting-edge research and real-world applications in robotics for asset inspection and management. In the context of this workshop, an “asset” refers to any valuable physical resource or piece of infrastructure that requires regular monitoring, maintenance, or management to ensure its proper functioning and longevity. While robotic inspection has made significant progress in recent years, many challenges remain unresolved when translating these innovations into practice. With invited talks from both world-leading researchers and industry representatives, this workshop will discuss the real problems faced by industry professionals and highlight the research at the forefront of addressing these problems. The outcome will be a clearer understanding of the open challenges in this field and a roadmap for future developments that meet industry expectations.
Important Dates:
- Paper Submission Deadline: TBD
- Notification to Authors: TBD
- Camera-Ready Deadline: TBD
- Workshop Date: TBD
Themes:
Our confirmed participants and speakers bring a distinct combination of expertise spanning various robotic research areas and industrial applications, offering a unique opportunity to discuss relevant topics such as:
Exploring the Future of Robotic Platforms: The workshop will explore the types of robots needed for diverse asset management tasks, including walking robots for rough terrains, flying drones for aerial inspections, crawling or climbing robots for hard-to-reach areas, and swimming robots for underwater inspections. The discussion will focus on designing versatile robots capable of adapting to a wide range of environments.
Sensing Capabilities for Effective Monitoring: Modern asset management requires advanced sensing capabilities to detect and predict issues before they become critical. The workshop will examine multimodal sensing approaches—incorporating sound, thermal imaging, multispectral analysis, and more—to ensure comprehensive data collection. We will also address the importance of active and adaptive sensing, enabling robots to adjust their data-gathering techniques based on real-time conditions.
Intelligent Data Collection and Path Planning: Gathering inspection data intelligently is crucial for efficient monitoring. Robots must collect data on demand, intensify data collection when anomalies are detected, and follow informative path planning to ensure all critical areas are covered. This session will delve into strategies for optimising robot behaviour, ensuring that inspections are thorough and data is collected precisely where and when it is needed.
Data Processing and Digital Twins: Effective asset management requires not only data collection but also seamless integration with advanced processing platforms. This workshop will explore the role of digital twins—virtual replicas of physical assets that store and process data for ongoing analysis. We will discuss how robots can be integrated into these digital systems, enabling real-time monitoring and long-term maintenance planning.
Enhanced Data Representation for Deeper Insights: Beyond traditional 3D models, digital twins for asset management benefit from additional data dimensions. These include the temporal aspect (tracking changes over time), contextual information (environmental conditions) and behavioural data (predicting how the asset will perform in various scenarios). We will discuss how these dimensions enhance decision-making and optimise asset lifecycle management.
Call for Papers:
To be announced.
Invited Speakers:
- Ian Manchester, University of Sydney
- Maurice Fallon, University of Oxford
- Timothy Barfoot, University of Toronto
- Jeannette Bohg, Stanford University
- Davide Scaramuzza, ETH Zurich
- Keiji Nagatani, University of Tokyo
- Dinesh Manocha, University of Maryland
- Andrew Scott, BHP
- Sam Seifert, Boston Dynamics
- Lashika Medagoda, Abyss Solutions
- Michael Bewley, Nearmap
Tentative Schedule:
Organisers:
- Viorela Ila, The University of Sydney, Australian Robotic Inspection and Asset Management Hub (ARIAM)
- Ian Manchester, The University of Sydney, ARIAM
- Donald Dansereau, The University of Sydney, ARIAM
- Rahul Shome, Australian National University (ANU), ARIAM
- Thierry Peynot, Queensland University of Technology (QUT), ARIAM
- Dimity Miller, Queensland University of Technology (QUT), ARIAM
- Stefan Leutenegger, Technical University of Munich (TUM), Boltzmannstrasse, Garching, Germany
- David Flynn, Robotics and Artificial Intelligence for Net Zero Infrastructure (RAINZ), University of Glasgow, Glasgow, United Kingdom
- Jaime Valls Miro, Ikerbasque Research Professor, AZTI, Basque Foundation for Science, Bilbao, Spain
Workshop Contact:
Please direct all your queries to:
ariam.hub@sydney.edu.au