"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.
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