An autonomous and intelligent robotic system for post-earthquake search, rescue and building condition assessment
Summary: Fast search & rescue (S&R) and emergency assessment of building conditions are critical in the case of major earthquakes. Current practices are, however, often conducted by human, which is labour intensive, dangerous and subject to errors. The project aims to analyse the feasibility of developing an intelligent robotic system prototype that can perform efficient post-earthquake S&R and emergency assessment of building conditions by applying various state-of-art digital technologies. It focuses on understanding New Zealand needs and testing technologies to develop an overall framework for the proposed robotic system. Funder: Building Research Association of New Zealand (BRANZ) Team: Yang Zou (PI), Jason Ingham (University of Auckland) Duration: 2020
Jan 1, 2020
Rapid post-earthquake assessment of bridge damage through 3D BIM reconstruction
Summary: In the aftermath of major earthquakes, rapidly capturing and quantifying the extent and severity of damage on buildings and critical infrastructure plays an important role in post-earthquake operations such as search and rescue, emergency repairs and long-term reconstruction. Current damage assessment practices, however, are labour intensive, time consuming and subject to errors, which also raise safety concerns for those engineers undertaking the inspections. To overcome this challenge, this project aims to develop a rapid, automated and data-driven method for post-earthquake bridge inspection by using Building Information Modelling (BIM) and 3D reconstruction. New algorithms are developed to reconstruct and analyse as-damaged bridge BIM to identify bridges’ damage grade and support decision making. To support further analysis, an Information Interpretation Engine (IIE) is developed to transform as-damaged BIM data to engineering analysis applications. Success of this project will not only add fundamental knowledge to post-earthquake damage assessment but significantly improve current engineering practice in New Zealand and worldwide. Funder: University of Auckland Faculty Research Development Fund (FRDF): New Staff Grant Team: Yang Zou (PI), Vicente Gonzalez (University of Auckland), James Lim (University of Auckland) Duration: 2019-2022
Jan 1, 2018