FURI | Fall 2022

Analysis of Previously Published Works Focused Around SLAM to Develop an Autonomous Self-Driving Formula Electric Vehicle

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The research is focused around using and modifying previously existing algorithms to allow for the ability to equip a formula electric vehicle with self-driving capabilities. The approach that will be taken is referred to as simultaneous localization and mapping (SLAM). In summary, this approach is aimed at building a map of an unknown environment while simultaneously traversing the environment at a quick speed. The only input that the algorithms will receive is a video feed from a Raspberry Pi camera module. From this data, the algorithm will plot the locations of cones on a track and develop a best-fit path.

Student researcher

Harry DeCecco

Computer science

Hometown: Havertown, Pennsylvania, United States

Graduation date: Fall 2022

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