Parrot Minidrone Competition EMEA 2021 This repository consist of all the work done on the Parrot Mini9drone competition by team ArIES.

DESCRIPTION- The aim of the competition is to get an introduction to Model-Based Design while challenging your peers. We designed a line follower algorithm using Simulink and learn how to model, simulate, and fly a minidrone.

MODEL- The whole model works in the following sequence

IMAGE PROCESSING- PARROT Image Conversion- converts an image from Y1UY2V format to three-channel RGB format. Binarization- Allows us to obtain the Binary image. Filter- Removes the noise pixels. Makes the contours of the path smoother and continuous. Borderless- Removes the objects that touch the image’s borders. During the landing phase, the final portion of the path will not be visible in this image. Filter_C_Det- detects the final circle when almost centered gives output as “C_DET” Filter1- Filter1 generates signals corresponding to the increments in position. Discrete Filter and Gain- Normalization using Delay function and discrete filter. Gains make the movement smoother. Edge Detection and End Detection-  Edge or End of the line is detection.

PATH PLANNING- Butterworth 1 Order Filter- To remove noise from the x and y. x and y are further muxed Hovering & Tracking- Hovering function gives constant altitude. Tracking gives the x, y using the x, y from path tracking Switch to Slow Movement- When track ends switches drone to slow movement from tracking Switch to Landing- When circle is detected, switches from slow movement to landing Slow Movement- Gives reduced gain in x, y. Better detection of centre of landing circle Landing- Diables slow movement. Reduces altitude Position Signal Generation- Generates reference signal for controller. x, y from all three modes are summed

Praoblems Faced- 1-Initial error of “Out of bound Array Index” 2-Tried to force land the drone at the height of error 3-Later stored the x, y and slowly reduced the z