# Testing a Vision-Based Autonomous Drone Navigation Model in a Forest Environment
## 4 Results and Discussion
### Flight Direction Results  
To evaluate the flight directions of the drone, the coordinates \(x\) and \(y\) that appeared in the video were captured to calculate the navigation waypoint. The calculation was performed by using the formula in Equations (8) and (9) to calculate the waypoint. Two separate experiments were conducted to test whether the drone was able to fly and navigate in different directions, like north, south, east, and west, according to the obtained coordinates from the masking module. As shown in Table 2, 10 tests were conducted in the experiment by applying different positive and negative coordinates to the simulator. When the output results are more than 0, the drone will fly toward the north direction. If the output results are less than 0, the drone will fly toward the south direction. Similarly to the results in Table 3, the drone will fly in the west direction if the output results are less than 0, and it will fly in the east direction if the results are more than 0. In the frames shown in Figure 12, the guided waypoint is located correctly on the free path. However,the frames in Figure 13 show that the guided waypoint is located on an obstacle, which is considered a false result. The movements of the drone are always based on the guided waypoint navigation command. When the guided waypoint falls on the free path, the navigation command directs the drone to fly toward that area. Additionally, we collected several videos to test the proposed method. For each video, a total of 500 frames from the video sequence were processed to find the blue waypoint. The total number of positive and negative points was calculated for each video. Then, the accuracy rate of the algorithm was obtained by calculating the ratio of the number of frames, where the frame of the blue waypoint is correctly overlapped in the red region (\(n\)), to the total number of frames (\(N\)). The formula is as follows:  
\[Accuracy=\frac{n}{N}*100 \tag{10}\]  
There are six videos with 500 frames each, and the accuracy results are shown in Table 3. Overall, the experiments show higher accuracy in localizing the navigation point, with an average of 97.7%. To further demonstrate the performance of our proposed method, we conducted several simultaneous simulations on the APM drone simulator with the output from our system. In this experiment, we evaluated our proposed method by simulating autonomous drone navigation in a forest. To prove that our method can successfully develop scene understanding and provide precise navigation command to the drone, the trails of the drone were captured and plotted on an offline satellite map. In the navigation module, the ultimate goal of the blue waypoint is to determine a clear path for navigation. Essentially, the coordinates acquired from the proposed system are processed using the velocity-guiding function in the drone kit framework [33]. Hence, the drone is automatically guided by the navigation command and reacts to the surrounding obstacles in the scene. The simulations are graphically shown in Figures 14 and 15. All the simulations were set at the same starting point which is from Location A to Location B. Additionally, all of the simulations  
As shown in the first row of Figure 14, the drone can interpret the scene and navigate autonomously toward the north-east direction (Location A to B) in a straight path correctly. The input was taken from the drone camera based on the detected trees, and the masking module processed the image frames for waypoint guiding. Based on the simulated results, the masking module was able to process all 500 frames with 100% localized waypoint accuracy in Video 2. The second and third rows of Figure 14 depict the correct simulated trail of autonomous drone navigation in different directions. As shown in the figure taken from Video 3, the drone was able to navigate autonomously toward the north-west direction along a straight path correctly with 10% accuracy.