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It works only on linux.\n\n## Installation\n- OpenCv installation \n```\n$ sudo apt update\n```\n```\n$ sudo apt install libopencv-dev python3-opencv\n```\n- Install numpy\n```\npip3 install numpy\n```\n- Install aruco\n```\npip3 install aruco\n```\n## Keyboard to control Pluto\n- Up arrow : Forward\n- Down arrow : Backward\n- Left arrow : go left\n- Right arrow : go right\n- q : take_off\n- w : Increase height\n- s : Decrease height\n- e : land\n- a : yaw left\n- d : yaw right\n- j : trim left roll\n- l : trim right roll\n- i : trim front pitch\n- k : trim back pitch\n\n## Program Files\n- [task1](https://github.com/Adityakumar2004/team_ID_51_task1/tree/main/task1) : Performs ```task 1```, using the keyboard controls the pluto drone.\n- [rectangle_2](https://github.com/Adityakumar2004/inter_iit/blob/main/rectangle_2.py) : Performs ```task 2```, moving the drone in a rectangle. \n- [Aruco Marker OpenCV](https://github.com/Adityakumar2004/inter_iit/tree/main/Aruco%20Marker%20OpenCV): Performs the task 2 to detect the ```Aruco marker``` and returns the respective position coordinates.\n    - [CAMERA-CALIBARTION](https://github.com/Adityakumar2004/inter_iit/tree/main/Aruco%20Marker%20OpenCV/CAMERA-CALIBARTION):Camera calibration consists                                        in obtaining the camera intrinsic parameters and distortion coefficients. This parameters remain fixed unless the camera optic                                        is modified, thus camera calibration only need to be done once. For the same we have uploaded chessboard images in different-                                        different plane and angle. \n    - [POSE-ESTIMATION](https://github.com/Adityakumar2004/inter_iit/tree/main/Aruco%20Marker%20OpenCV/POSE-ESTIMATION): The camera pose relative to the                                        marker is a 3d transformation from the marker coordinate system to the camera coordinate system. It is specified by rotation and                                      translation vectors.\n    - [MARKER-DETECTION](https://github.com/Adityakumar2004/inter_iit/tree/main/Aruco%20Marker%20OpenCV/MARKER-DETECTION): We will apply the ArUco detector                                      with OpenCV’s cv2.aruco.detectMarkers function.\n    - [Pattern-PNG](https://github.com/Adityakumar2004/inter_iit/tree/main/Aruco%20Marker%20OpenCV/Pattern-PNG): Pattern png for camera calibration.\n    - [calib_data](https://github.com/Adityakumar2004/inter_iit/tree/main/Aruco%20Marker%20OpenCV/calib_data):As a result of the calibration, we get a                                          camera matrix: a matrix of 3x3 elements with the focal distances and the camera center coordinates, and the distortion c                                              coefficients: a vector of 5 or more elements that models the distortion produced by your camera.\n              \nFor Task 1 execute this file: task1.py from task1 folder\nFor task2 hover part execute this file: rectangle_hover.py from task2\nFor task2 for rectangle path execute this file: rectangle_final.py \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Froboticsclubiitj%2Fpluto_drone_interiit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Froboticsclubiitj%2Fpluto_drone_interiit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Froboticsclubiitj%2Fpluto_drone_interiit/lists"}