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Using Deep Neural Networks and Industry-Friendly Standards to Create a Robot Follower for Human Leaders

Gilliam, Austin Taylor

Abstract Details

2018, Master of Science, Ohio State University, Computer Science and Engineering.
In recent decades, there has been an increasing interest in the capability of a robot follower for both human and robot leaders. In the case of a human leader, there is sometimes a requirement of additional sensors, GPS tracking, or WIFI capability. While these solutions may produce the desired results, they are often unrealistic for industry, particularly when using off-the-shelf hardware, or when WIFI or GPS is not available. This work describes an industry-friendly robot follower, which utilizes only a mobile device, camera, and Deep Neural Network (DNN) to keep pace with a designated human leader. We do this by collecting inertial data from the leader’s mobile device, which is then transferred to the robot’s server via Bluetooth. This data is combined with a corresponding video from the robot’s camera, which is then analyzed using a DNN to classify the action the robot should take. These components in tandem result in a robust following system, which can be minutely tweaked for a variety of scenarios and requirements.
Dong Xuan (Advisor)
Feng Qin (Committee Member)
35 p.

Recommended Citations

Citations

  • Gilliam, A. T. (2018). Using Deep Neural Networks and Industry-Friendly Standards to Create a Robot Follower for Human Leaders [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524150398390964

    APA Style (7th edition)

  • Gilliam, Austin. Using Deep Neural Networks and Industry-Friendly Standards to Create a Robot Follower for Human Leaders. 2018. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1524150398390964.

    MLA Style (8th edition)

  • Gilliam, Austin. "Using Deep Neural Networks and Industry-Friendly Standards to Create a Robot Follower for Human Leaders." Master's thesis, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524150398390964

    Chicago Manual of Style (17th edition)