Reference number : GC-2017-Q3-00449, amendment number : , agreement type : G, recipient legal name : Ramirez-Serrano, Alejandro (University of Calgary), recipient country : CA, recipient province : nan, recipient city : Alberta, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Capital projects employ engineers to design assets based on project plans. Parts are built in factories all over_x000D_
the world and shipped to site which in numerous occasions do not fit to the existing infrastructure. These and_x000D_
other factors cost the capital project industry $1.6 Trillion annually. Using a revolutionary and comprehensive_x000D_
end-to-end software solution to solve the problem of industrial rework and facilitate proactive, cost effective_x000D_
project execution digital project information generated via the collection of a variety of sensory and spatial data_x000D_
to create a Digital Twin of the physical project is currently being used. However, data collection, typically_x000D_
performed manually, requires to be automated to enable effective capital project execution while maintaining_x000D_
the required sensor data accuracy._x000D_
By identifying mismatches between reality and plan, the automated sensor data collection will enable corrective_x000D_
actions early in the project execution before they cause rework._x000D_
The focus of this project is to automate capital project fast data collection in high definition via the use of_x000D_
autonomous Unmanned Ground Vehicles (UGVs)._x000D_
In particular we will develop enhanced robot's obstacle avoidance mechanisms to better estimate sensor_x000D_
placement and maneuvering the UGV to optimally position the sensors for relevant and accurate data_x000D_
collection. A vision input (LIDAR sensor) will be used as a feedback to servo the UGV for 3D motion_x000D_
purposes while having the capabilities to quickly identify precise sensor placement. The focus is on developing_x000D_
tools for (1) accurate detection of complex obstacles typically found in commercial sites (e.g., overhand_x000D_
cables), (2) UGV path planning for optimal sensor placement via visual servoing/surveying, and (3) analyze the_x000D_
effectiveness of the use of UGVs in construction sites., program purpose french : Capital projects employ engineers to design assets based on project plans. Parts are built in factories all over_x000D_
the world and shipped to site which in numerous occasions do not fit to the existing infrastructure. These and_x000D_
other factors cost the capital project industry $1.6 Trillion annually. Using a revolutionary and comprehensive_x000D_
end-to-end software solution to solve the problem of industrial rework and facilitate proactive, cost effective_x000D_
project execution digital project information generated via the collection of a variety of sensory and spatial data_x000D_
to create a Digital Twin of the physical project is currently being used. However, data collection, typically_x000D_
performed manually, requires to be automated to enable effective capital project execution while maintaining_x000D_
the required sensor data accuracy._x000D_
By identifying mismatches between reality and plan, the automated sensor data collection will enable corrective_x000D_
actions early in the project execution before they cause rework._x000D_
The focus of this project is to automate capital project fast data collection in high definition via the use of_x000D_
autonomous Unmanned Ground Vehicles (UGVs)._x000D_
In particular we will develop enhanced robot's obstacle avoidance mechanisms to better estimate sensor_x000D_
placement and maneuvering the UGV to optimally position the sensors for relevant and accurate data_x000D_
collection. A vision input (LIDAR sensor) will be used as a feedback to servo the UGV for 3D motion_x000D_
purposes while having the capabilities to quickly identify precise sensor placement. The focus is on developing_x000D_
tools for (1) accurate detection of complex obstacles typically found in commercial sites (e.g., overhand_x000D_
cables), (2) UGV path planning for optimal sensor placement via visual servoing/surveying, and (3) analyze the_x000D_
effectiveness of the use of UGVs in construction sites., agreement title english : Safe robot navigation and infrastructure data capture within commercial environments via optimal positioning of sensors, agreement title french : Safe robot navigation and infrastructure data capture within commercial environments via optimal positioning of sensors, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-11-08, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada