Experiment Design

This week, I hope to write my own usability study, similar to the study in "Interactions and Training with Unmanned Systems and the Nintendo Wiimote". Here are some of the basic ideas/changes I would implement:

-The obstacle course would involve tasks like moving blocks from place to place, and steering around specially marked areas.
-The participants would still receive training, and then perform the obstacle course 3 times per control scheme.
-Participants would navigate the robot through the obstacle course using 2 (rather than 3) control schemes: iPhone and "controller" (some sort of standard controls for the specific type of robot being driven).
-The questionnaire would include the following questions (5-level Likert scale):

1. Instructions on how to perform gestures were clear

2. Gestures were easy to learn

3. Gestures were easy to remember/recall

4. Gestures were easy to perform

5. The Gestures performed did not cause my hands, arms, shoulders and/or wrists to become fatigued

6. The iPhone was easy to hold and use

7. The system recognized the gestures accurately

8. Controlling the vehicle through gestures was easy

9. Controlling the vehicle through the iPhone was easy

10. Controlling the vehicle through the "controller" was easy

The study will be very similar to the one from the paper. Eventually, there will be more detailed outlines of the study's procedures. Stay tuned, and as always, any suggestions are welcome!

Lauren

Paper: Daniel Barber

Eventually (hopefully this semester), there will come a time when the iOS Gesture Controls become a fully-fledged, standalone system. At that time, we will hopefully reach out to our friends at UCF to do some user studies in order to gauge the effectiveness of the system. There has been a study already in Wiimote-based Gesture Controls, called "Interactions and Training with Unmanned Systems". This study, because it is very similar to the iOS project, will be the basis for my study when I design it.

"Interactions and Training with Unmanned Systems" used a Wiimote, rather than an iPhone to control the robot. There were three different control schemes implemented: Traditional Joystick Control, Accelerometer/Motion Steering Wheel Style Control, and Hand and Arm Gestural Control. The joystick control utilizes only the D-pad, for thrust/steering. The accelerometer control is similar to the the controls from Mario Kart Wii (using the Wiimote sideways like a steering wheel, pressing 2 to accelerate). The main difference is that there is an added axis of rotation: tilting the remote along the Z-axis controls the speed at which the robot moves. The gestural control is the most similar to the iOS controls. Their system uses a machine learning algorithm comprising a linear classifier and 29 features based on a 2D pen-based gestures. They used 4 gestures: Move Forward, Turn Left, Turn Right, Stop.

The usability study that the researchers conducted involved using each of the three control styles to navigate a robot through an obstacle course. The runs were timed, and then the participant complete the following questionnaire (5-level Likert scale):

1. Instructions on how to perform gestures were clear

2. Gestures were easy to learn

3. Gestures were easy to remember/recall

4. Gestures were easy to perform

5. The Gestures performed did not cause my hands and/or writes to become fatigued

6. The Wiimote was easy to use

7. The system recognized the gestures accurately

8. Controlling the vehicle through gestures was easy

9. Controlling the vehicle through the Wiimotes's motion tracking was easy

10. Controlling the vehicle through the Wiimote's directional pad was easy

They also ranked their preferred controls, and gave additional feedback about their experience.