Title

Design And Implementation Of Human-To-Swarm Robotics Simulator And Interface

Author(s)

Michael Ott

School Name

Governor's School for Science and Math

Grade Level

12th Grade

Presentation Topic

Engineering

Presentation Type

Mentored

Mentor

Mentor: Dr. Wang; Department of Mechanical Engineering, Clemson University

Abstract

The purpose of our research was to test the interaction between humans and swarm robots along with using the new EEG sensor. For this study, an omnidirectional robot for use in Gazebo, the 3D simulator used for our research, was chosen. A joystick control was developed to control a leader robot within the swarm using velocity commands. A control system was then implemented to sync these robots together using velocity and position feedback loops, and simple collision detection was added. Then, an interface with the new EMOTIV EEG sensor was developed in order to both control the robots and to test for cognitive load on the teleoperator. The EEG sensor was able to send unidrectional commands to the robots. After the EEG sensor was correctly interfaced with, cognitive load of the human teleoperator was tested under varying conditions using the EEG device. Different situations such as varying topologies or number of robots was used to test changes in cognitive load of the human. Based on the results, the frustration signal was a good indicator of the cognitive load.

Location

Owens G07

Start Date

4-16-2016 1:30 PM

COinS
 
Apr 16th, 1:30 PM

Design And Implementation Of Human-To-Swarm Robotics Simulator And Interface

Owens G07

The purpose of our research was to test the interaction between humans and swarm robots along with using the new EEG sensor. For this study, an omnidirectional robot for use in Gazebo, the 3D simulator used for our research, was chosen. A joystick control was developed to control a leader robot within the swarm using velocity commands. A control system was then implemented to sync these robots together using velocity and position feedback loops, and simple collision detection was added. Then, an interface with the new EMOTIV EEG sensor was developed in order to both control the robots and to test for cognitive load on the teleoperator. The EEG sensor was able to send unidrectional commands to the robots. After the EEG sensor was correctly interfaced with, cognitive load of the human teleoperator was tested under varying conditions using the EEG device. Different situations such as varying topologies or number of robots was used to test changes in cognitive load of the human. Based on the results, the frustration signal was a good indicator of the cognitive load.