Improving Subsurface Non-metallic Utility Locating Using Self-Aligning Robotic Ground Penetrating Radar

Main Objective: ULC Robotics will develop a pre-commercial prototype robotic locating system that will reduce accidental penetration of buried utilities. This will be achieved by improving the quality of image and location data using self-adapting antenna configurations that increase the probability of detection. Two robotic carts will autonomously align themselves to each other and to the buried utilities to obtain the best Signal to Noise Ratio. By automating sensor scanning, data processing, and locating, the operator training requirements will be minimized, and the cost of deployment will be much lower compared to existing GPR locating services. First, representative burial conditions will be studied through numerical simulations to assess GPR performance in varying antenna configurations. This will be used as input to path planning logic for autonomous operation. Software will be developed for data collection, control and command, data processing, and data visualization. The robotic carts will be designed, fabricated, and tested. Various techniques to improve image quality during the scanning processes will be employed which will be implemented in software and control. ULC will test the prototype at utility partners' sites and determine improvements that will accelerate the transition of the prototype to a commercial product. Combining low-risk robotic technologies and known antenna scanning techniques will rapidly make this solution commercially available. Most importantly, the increased probability of detection will reduce the chances of third-party damage during excavation and improve public safety. Public Abstract: Ground Penetrating Radar (GPR) is used extensively for locating underground pipelines and preventing third-party damage. ULC Robotics has tested and evaluated a promising method for deploying GPR in urban and rural areas that will maximize Signal-to-Noise ratio, increase the probability of detection, and reduce false alarms. Using commercially available GPR and a custom robotic mobile platform, scanning will be performed through automatic antenna alignment and path planning. Object detection and classification will filter out the clutter and surrounding objects. An intuitive user interface will render 3D objects that will improve the identification of the target asset and other neighboring utilities while minimizing operator's training requirements. A robotic mobile platform will allow for increased consistency in scanning and signal interpretation while enabling automatic generation of utility maps. This project co-funded by the Pipeline and Hazardous Materials Safety Administration (PHMSA) will focus on developing the prototype robotic system which will subsequently be followed by rapid commercialization. During the project, numerical simulation and testing will be performed to determine the optimal antenna configurations required for varying pipe geometries, burial depths, and soil conditions. The robotic platform and sensing system will be designed, fabricated, and tested at ULC Robotics. After completing the prototype development, the robotic system will be tested in the field to demonstrate its improved locating capabilities. The robotic system will provide enhanced locating capabilities for both metallic and non-metallic pipelines.

Language

• English

Project

• Status: Active
• Funding: $393690
• Sponsor Organizations:

  Pipeline and Hazardous Materials Safety Administration

  U.S. Department of Transportation
  East Building, 2nd Floor 1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Principal Investigators:

  Shah, Aalap

  Ren, Baiyang

• Start Date: 20190930
• Expected Completion Date: 0
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Antennas; Detection and identification technologies; Ground penetrating radar; Prototypes; Robots; Simulation; Underground utility lines
• Subject Areas: Data and Information Technology; Energy; Highways; Pipelines;

Filing Info

• Accession Number: 01754233
• Record Type: Research project
• Source Agency: ULC Robotics
• Files: RIP, USDOT
• Created Date: Oct 5 2020 4:12PM