With vast improvements in computing power in the last two decades, humans have invested significantly in engineering resources in an attempt to automate labor intensive or dangerous tasks. A particularly dangerous and labor-intensive task is painting lines on roads for facilitating urban mobility. This thesis proposes an approach to automate the process of painting lines on the ground using an autonomous ground vehicle (AGV) fitted with a stabilized painting mechanism. The AGV accepts Global Positioning System (GPS) coordinates for waypoint navigation. A computer vision algorithm is developed to provide vision feedback to stabilize the painting mechanism. The system is demonstrated to follow an input desired trajectory and cancel any high frequency vibrations due to the uneven terrain that the vehicle is traversing. Also, the stabilizing system is able to eliminate the long-term drift (due to inaccurate GPS waypoint navigation) using the complementary vision system. / MS / There is a need to develop an automated system capable of painting lines on the ground with minimal human intervention as the current methods to paint lines on the ground are inefficient, labor intensive, and dangerous. The human input to such a system is limited to the determination of the desired trajectory of the line to be drawn. This thesis presents the design and development of an autonomous line painting system that includes an autonomous ground vehicle (capable of following GPS waypoints) integrated with an automatic line painting mechanism. As the vehicle traverses the ground, it experiences disturbances due to the interaction between the wheels and the ground, and also a long-term drift due to inaccurate tracking of the input GPS coordinates. In order to compensate for these disturbances, a vision system is implemented providing feedback to a stabilizing arm. This automated system is able to demonstrate the capability to follow a square trajectory defined by GPS coordinates while compensating for the disturbances.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/87564 |
| Date | 08 February 2019 |
| Creators | Nagi, Navneet Singh |
| Contributors | Mechanical Engineering, Leonessa, Alexander, Southward, Steve C., Akbari Hamed, Kaveh |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0182 seconds