Presentation Title

Unmanned Ground Vehicle for Water Leaking Detection

Faculty Mentor

yangquan chen

Start Date

23-11-2019 8:45 AM

End Date

23-11-2019 9:30 AM

Location

168

Session

poster 2

Type of Presentation

Poster

Subject Area

engineering_computer_science

Abstract

The Unmanned Ground Vehicle (UGV) project is the future of the next generation’s agricultural gadgets. Instead of the past’s archaic methods of manually searching for leaks with acoustic procedures, the UGV project hopes to replace the previous methods with a more strategic appliance – a powerful camera attached to a fully autonomous vehicle. Utilizing a combination of dynamic image-processing techniques and mobilization, this rover-camera duo is able to autonomously navigate through waypoints and detect pipe leaks more frequently, efficiently, and accurately than a field worker would. Powered and guided by the Mission Planner program and the Pixhawk Autopilot System, the rover is capable of decreasing overhead costs, and most importantly, aiding in the preservation of water. The project’s state of the art features is distinguished by its data collection platform, algorithm design, and user-friendly interface.

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Nov 23rd, 8:45 AM Nov 23rd, 9:30 AM

Unmanned Ground Vehicle for Water Leaking Detection

168

The Unmanned Ground Vehicle (UGV) project is the future of the next generation’s agricultural gadgets. Instead of the past’s archaic methods of manually searching for leaks with acoustic procedures, the UGV project hopes to replace the previous methods with a more strategic appliance – a powerful camera attached to a fully autonomous vehicle. Utilizing a combination of dynamic image-processing techniques and mobilization, this rover-camera duo is able to autonomously navigate through waypoints and detect pipe leaks more frequently, efficiently, and accurately than a field worker would. Powered and guided by the Mission Planner program and the Pixhawk Autopilot System, the rover is capable of decreasing overhead costs, and most importantly, aiding in the preservation of water. The project’s state of the art features is distinguished by its data collection platform, algorithm design, and user-friendly interface.