Led by one of CNAM’s new professionals, this webinar will showcase the emerging research and analysis being undertaken to advance the asset management body of knowledge. This event is an opportunity for new and seasoned professionals alike to gain new knowledge in a particular area of research.

Details

Despite advances in automatic indoor progress monitoring and quality control using images, the required visual data is still captured manually. Camera-equipped rotary unmanned aerial vehicles (UAVs) have received remarkable attention for their applications in automated visual site inspection and data collection in the construction community. However, autonomous navigation and localization of UAVs have remained challenging in indoor construction environments where the global positioning system (GPS) signals are denied or unreliable. Construction sites are ever-changing, often cluttered environments that include temporary objects as well as low-texture and repetitive areas. These weaken the robustness of most feature-based solutions such as visual simultaneous localization and mapping (vSLAM). This research aims to present a low-cost tag-based indoor localization and navigation method for off-the-shelf UAVs equipped with a minimum sensor suite of an onboard monocular camera and an inertial measurement unit (IMU).

Learning Objectives

1) What are the opportunities and challenges of using mobile robots for jobsite data collection?
2) How tag-based autonomous navigation can be used for infrastructure monitoring and visual inspections?
3) Why is autonomy challenging indoors?
4) What is tag-based indoor localization? What are the advantages and where can we use it?
5) What are the current cutting-edge robotic solutions?

Moderator

S. Madeh Piryonesi, PhD, Paraw Inc.

Speaker

FREE

Navid Kayhani is a Ph.D. student in the Department of Civil and Mineral Engineering at the University of Toronto. He is currently working with Prof. Brenda McCabe (Department of Civil and Mineral Engineering) and Prof. Angela Schoellig (University of Toronto Institute for Aerospace Studies).  Navid’s research interests are related to automation and robotics in construction and infrastructure. Formerly, he was a research assistant at Tecnosa R&D center at the University of Tehran, Iran. Navid was involved in a number of projects, including (1) the development of an integrated crane management system for modular construction, (2) Virtual Reality (VR)-enabled heavy lift planning, both in cooperation with PCL Industrial Management Inc. (Edmonton, Canada); and (3) the development of a stochastic framework to automate the runway rehabilitation workface planning of Mehrabad International Airport, Tehran, Iran. Currently, he is working on the applications of autonomous aerial robots (also known as drones) in automated indoor data collection. The main focus of his Ph.D. is on indoor localization and autonomous navigation of aerial robots for progress tracking and schedule updating of under-construction buildings.

Madeh has a PhD in infrastructure asset management. He is interested the application of data analytics to infrastructure asset management especially levels of service and climate change adaptation.

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