Advanced UAV

IMG_0303This year YUAA will take on an advanced project for highly experienced members. This team aims to design and build an autonomous aircraft and will build on skills from last year’s UAV project.

The team is registered to compete in the Association for Unmanned Vehicle Systems International (AUVSI) Seafarer Chapter’s 13th Annual Student Unmanned Air Systems (SUAS) Competition, scheduled to take place June 17th-21st. The competition consists of various flight missions, including target recognition, payload drops, and flight through GPS-bounded coordinates, all of which are to be performed autonomously by the UAV.

The team spent the first semester planning the layout of the UAV, deciding the proper equipment to order, such as camera and camera mounts, and considering payload drop mechanisms. When asked what the most difficult task was prospected to be, team captain Thomas Ryan answered that equipping and programming the UAV to accomplish all of the flight missions in the competition certainly would be, which is the grand objective of this team’s project. They have already installed an auto pilot into the UAV and added airspeed sensors on the tip of the wings and have had two test flights; one occurred at the end of January and another at the beginning of February, both of which were very successful. To ensure safe landing in the snow during the first flight, the team built skis for their aircraft. 20150125_102300

During the second test flight, the team tested features of the UAV’s autopilot system. Team member Antonio Martinez has been using the Ardupilot Mission Planner software to communicate with the receiver on the UAV. Ryan commented that they have been taking off and landing the plane with a controller, but once the UAV is in the air, he switches the setting on the remote to an automated mode and everything else that the UAV does is completely laissez-faire. Eventually, Ryan says, the UAV will be able to take off and land on its own. In this test flight, the UAV successfully flew to designated GPS coordinate points and circled the location in a fixed given radius.

In the upcoming months, the team’s goal is to take data from a camera (that will be attached to the plane) and locate GPS points through advanced image processing. By doing so, the team should learn where the plane is and where the plane is heading in real time. Additionally, the team will design a complex algorithms process that will allow the UAV to identify ground targets and drop payloads upon detection.

Stay tuned for team updates!

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Thomas Ryan is a Junior Biomedical Engineering Major and will be leading the advanced project. He is also YUAA’s Chief Engineer.