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Author : Christopher Xu Palo Alto High School, Palo Alto, CA, United States Abstract Swerve drive robots are highly maneuverable robots suited for operating indoors, but are difficult to control due to their large number of actuators: 8 independently controlled motors where certain combinations of inputs cause the motors to oppose each other and drastically decrease efficiency. This study aims to gain new understandings about tackling the problem of overconstraint, having more inputs than the robot’s degrees of freedom, while being intuitive for humans to control and capable of agile movements. A 2D simulation of a robot in a maze was created with different control modes with varying numbers of inputs, and participants were asked to submit their fastest time and rate each mode. The results show that many inputs slowed down operation considerably while few little inputs, although fast to learn, were too restrictive. These results agree with the existing body of knowledge that too many degrees of freedom in the controls decrease operator efficiency and suggest that there is an optimal number of inputs in between that is the easiest to learn, while reaping the full benefits of a maneuverable drivetrain. Research Paper : 
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