User Experience

User Test Report: ArUco Marker Detection (Ralph Adrichem)

Objective: To evaluate the usability and functionality of ArUco markers' detection using a camera interface displaying their ID and coordinates for user understanding.

Test Method: I conducted a user test to assess the effectiveness of ArUco marker detection. Users interacted with the system, observing the camera feed displaying detected ArUco markers, their ID, and corresponding coordinates.

Findings:

Positive Aspects:

Detection Accuracy: The system accurately identified ArUco markers and displayed their IDs, allowing users to distinguish between different markers.
Coordinate Display: Users found the presentation of coordinates alongside the markers informative, aiding in spatial understanding.
Real-time Detection: The real-time display of marker IDs and coordinates was appreciated, providing immediate feedback.

Areas for Improvement:

Orientation Feedback: While the IDs and coordinates were displayed effectively, users expressed interest in understanding the markers' orientations for better spatial comprehension.
Enhanced Marker Visualization: Implement techniques to improve marker visibility and reflection for clearer detection.
If the markers are not properly lighted the markers won't be detected as good.

Conclusion:

The system showed promising accuracy in detecting ArUco markers and presenting their IDs and coordinates. Enhancements in marker visualization, orientation feedback, and user interface refinement could further improve the user experience and comprehension.

User Test Report: Empty spot detection (Calvin Nessen)

Objective: The primary objective of this script is to offer a user-friendly solution for real-time detection and visualization of different shades of white in a live camera feed. Specifically, it aims to assist the Human Collaborative Drawing Robot in identifying empty spots within the observed scene.

Test Method: I conducted a user test to assess the effectiveness of the white spot detection. Users interacted with the system, observing the camera feed displaying detected white spots, coordinates and the center point of each detected area.

Findings:

Positives:

Effective Detection: The script successfully identifies and highlights different shades of white, meeting the objective of detecting potential empty spots.
Visual Clarity: Bounding rectangles and centroid markers enhance the visual representation of detected areas, providing users with clear indicators.

Negatives:

Limited Adaptability: The reliance on hardcoded camera resolution settings may hinder adaptability to diverse lighting conditions or varied camera capabilities, impacting the overall user experience.
Overlapping Contours: In scenarios with closely situated empty spots, the script may produce overlapping contours, potentially complicating the interpretation of individual areas.

Conclusion:

The script provides a functional solution for detecting empty spots based on various shades of white in a live camera feed. However, users should be aware of potential limitations related to adaptability and the possibility of overlapping contours in certain scenarios. Experimenting with script parameters is recommended for optimal performance in different environments.

Color Detection with Rubik's Cube and Color Markers (Ralph Adrichem)

Testperson: Peter Adrichem, age 59

In my test, i explored how well the system identified + tracked colors drawn on a Rubik's Cube. Here's what i found:

The test person found the colors accurately tracked on the screen, making it easy for them to track and identify each color.

They noted that the system's display of coordinates alongside the colors helped in understanding the precise locations of each color on the Rubik's Cube.

Feedback

Overall, the test person found the color detection to be quite effective. However, they noticed occasional challenges in differentiating similar shades, especially in complex lighting conditions.

They observed that the system's accuracy was impacted by changes in lighting, such as shadows or uneven illumination, affecting color detection reliability.

Conclusion:

The system showed promise in displaying colors on the Rubik's Cube, but there were challenges under specific conditions. Although it was found useful overall, improvements in handling similar shades and adapting to different lighting conditions would enhance its reliability and user-friendliness.

docs/learning_stories/ralphadrichem.md

User Test Report: Red Color Detection (Ralph Adrichem)

Testperson: Ilse Tromp, age 24

Objective:

To evaluate the usability and functionality of red color detection using a red marker. The system should accurately detect the red color, display its coordinates in the console, and overlay this information within the camera frame for visual feedback.

Test Method:

I conducted a user test to assess the effectiveness of red color detection. Users interacted with the system, observing the console output displaying detected red color coordinates and the real-time camera feed with overlaid information.

Positives:

Color Accuracy: The system accurately identified the red color from the marker, providing reliable results during the test.
Coordinate Display (Console): Users appreciated the presentation of coordinates in the console, allowing for easy reference and integration into other systems.
Real-time Visualization (Camera Frame): The overlay of red color detection information within the camera frame was positively received, offering a visual confirmation of the detected color.

Negatives:

Coordinate Formatting: Users suggested a clearer formatting of coordinates, such as adding labels or units for better understanding.

Conclusion

The system demonstrated effectiveness in detecting the red color from the marker, presenting coordinates in the console, and overlaying information within the camera frame. Addressing the suggested improvement for coordinate formatting would enhance the overall user experience and make the system more versatile for different scenarios.

User Test Report: Drawing surface (Calvin Nessen)

Objective:

To evaluate the ease of use of the drawing setup.

Test Method: I conducted a user test to find out if the drawing setup is easy to use and where there is room for improvement with the drawing setup.

Findings

Positives:

Surface: the surface is great to draw on and big enough to draw together with the robot.
Easy Removal and Reusability: Demonstrate the ease of removing drawings from the whiteboard surface. Confirm that the whiteboard foil allows for effortless erasure, and the MDF sheet maintains its integrity for repeated use.

Negatives:

Foil Adhesion Issues: Intentionally create air bubbles or wrinkles during the foil application process. Evaluate if such imperfections affect the overall functionality of the drawing surface and the system's performance.

Conclusion

While the drawing setup exhibits commendable features such as a spacious surface and easy reusability, addressing foil adhesion issues is crucial for enhancing overall user satisfaction and system performance. Future iterations or improvements should focus on refining the foil application process to eliminate imperfections and deliver a consistently smooth drawing surface.

User Test Report: Integrated Detection Script (Calvin Nessen)

Testperson: Random ICT Student, age 23

Objective:

The objective of this user test is to ensure that all the working components of the project are integrated into one script, allowing users to run a single script to access all functionalities and view the detection data on the camera feed.

Test Method:

I conducted a user test to assess the effectiveness of the integrated script. Users interacted with the system, observing the console output displaying detected red color coordinates, sending data to the mqtt and the real-time camera feed with overlaid information.

Random ICT Student testing the integrated script

Positives:

Successful integration of all components into one script.
Correct functioning of all functionalities.

Negatives:

Smoother detection: Detection could be less jumpy.