Solar power generation facilities require large areas of land in order to be effective, land that often can not be economically “paved over”; even the basic landscaping required to keep the grass from interfering with normal operations and maintenance is a significant expense when performed by humans. We have been sponsored by Duke Energy and OUC to develop an autonomous, intelligent robotic system capable of trimming around and underneath existing solar infrastructure. Most existing robotic landscaping products depend on installed infrastructure (such as invisible fences), preexisting data about their environment, and only basic sensors. While these systems are effective in residential settings, they are not very sophisticated or adaptable and would not perform well or be easily deployed in such large areas with preexisting commercial infrastructure. The eGOAT uses a variety of advanced sensors as well as Simultaneous Localization And Mapping (SLAM) and computer vision algorithms to create and maintain a detailed, up-to-date map of its environment. Regardless of how large, complex, or dynamic the environment may be, the eGOAT is intended to be deployed as a “fire-and-forget” system.
Rubin York - RYork@ouc.com