This repository is the working space of two project groups (Drone1 and Drone2) in the context of Robotic and Embedded Project (PRJREB), INSA Lyon.
Each group has a working directory (Drone1/ and Drone2/), shared ressources areto be found in the main directory.

Installation Bebob
SIFT
SURF
Detection de contours
General bebop
Topic bebop

Build OpenCV: cmake -D CMAKE_BUILD_TYPE=RELEASE
-D OPENCV_ENABLE_NONFREE=ON

$ roslaunch bebop_driver bebop_node.launch

$ rostopic pub --once [namespace]/takeoff std_msgs/Empty

$ rostopic pub --once [namespace]/land std_msgs/Empty

$ rostopic pub --once [namespace]/reset std_msgs/Empty

linear.x  (+)      Translate forward
          (-)      Translate backward
linear.y  (+)      Translate to left
          (-)      Translate to right
linear.z  (+)      Ascend
          (-)      Descend
angular.z (+)      Rotate counter clockwise
          (-)      Rotate clockwise

(from https://www.learnopencv.com/video-stabilization-using-point-feature-matching-in-opencv/)

Video stream is published on image_raw topic as sensor_msgs/Image messages. (640 x 368 @ 30 Hz) (doc)
We receive one image after another, so we'll need to store at least one opencv image in a 'buffer'.
We need to convert this 'ROS styled' images flow to OpenCV format. We'll use ROS' package vision_opencv.

Tutorial on converting ROS images to OpenCV format (Python).

from cv_bridge import CvBridge
bridge = CvBridge()
cv_image = self.bridge.imgmsg_to_cv2(image_message, desired_encoding='passthrough')

We will need to pay attention to the encoding that we want, most common encoding for opencv is bgr8.

Because we don't really need colors

prev_gray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY) 

This method retrieve interesting points to track in the image, ie corners, straight lines, etc. You can change the number of points wanted, minimum space between them, etc.

• cv2.goodFeaturesToTrack() (doc))

This method try to track each given feature in the next frame, you have to clean the results because errors may appear.

• cv2.calcOpticalFlowPyrLK() (doc)

This methods uses the points of interest from the first frame, and the linked points of interest from the second frame to compute the transformation matrix.

ATTENTION : this method is deprecated since OpenCV-4, see cv2.estimateAffine2D() and cv2.estimateAffinePartial2D() instead.

• cv2.estimateRigidTransform() (doc)