Using a student-built quadcopter, the navigation capabilities of autonomous aerial vehicles were explored. The project implemented an artificially intelligent quadcopter that could autonomously identify, navigate to, and eventually land at a marked location. Through the use of an onboard camera and Raspberry Pi control board, image processing techniques were developed in Python in order to analyze and understand the quadcopter’s environment. By binarizing and contouring the image feed from the camera, a red landing target was identified. Using this environmental model, control algorithms were developed in order to intelligently navigate to and land on the target autonomously.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Gallenstein, Brian William
• Rosenblum, Yael

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-012815-223048

Advisor

• Rong, Yiming

Year

• 2015

Center

• Shanghai, China Project Center - MQP

Sponsor

• Shanghai University

Date created

• 2015-01-28

Location

• Shanghai

Resource type

• Major Qualifying Project

Major

• Robotics Engineering

Rights statement

• In Copyright