Hsieh, S. (2022, August), Remote Machine Vision Lab Design and Evaluation using AI based Mobile Robot  Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--40587

\bibitem{asee_peer_40587}
  Hsieh, S. (2022, August), \emph{Remote Machine Vision Lab Design and Evaluation using AI based Mobile Robot}
  Paper presented at 2022 ASEE Annual Conference \& Exposition, Minneapolis, MN.
  10.18260/1-2--40587

Sheng-jen Hsieh.  "Remote Machine Vision Lab Design and Evaluation using AI based Mobile Robot".  2022 ASEE Annual Conference & Exposition, Minneapolis, MN, 2022, August.  ASEE Conferences, 2022.  https://peer.asee.org/40587 Internet.  30 Apr, 2024

\bibitem{asee_peer_40587}
  Sheng-jen Hsieh.
  "Remote Machine Vision Lab Design and Evaluation using AI based Mobile Robot".
  \emph{2022 ASEE Annual Conference \& Exposition, Minneapolis, MN, 2022, August}.
  ASEE Conferences, 2022.
  https://peer.asee.org/40587 Internet.  30 Apr, 2024

@INPROCEEDINGS{asee_peer_40587
author = "Sheng-jen Hsieh"
title = "Remote Machine Vision Lab Design and Evaluation using AI based Mobile Robot"
booktitle = "2022 ASEE Annual Conference \& Exposition"
year = "2022"
month = "August"
address = "Minneapolis, MN"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/40587}
number = {10.18260/1-2--40587}
}

TY  - CPAPER
AB  - COVID-19 has made hands-on lab education a challenging task to achieve.  A remote lab was developed to overcome barriers such as equipment cost and limited lab time, and to provide authentic and self-paced learning experiences. This paper describes the development and preliminary evaluation of a remote lab for machine vision built upon an AI-based Cozmo robot.  Students were asked to (1) view a video on how to access the remote lab, (2) observe how the system works, and (3) execute a set of code to understand what will happen. They were then asked to modify the code to accomplish a more complex object recognition task. Preliminary results suggest that while they were very interested in learning more about the Cozmo robot platform, modifying the existing code to accomplish a new task was not straightforward.  Suggestions include providing more explanation about the existing code and providing assistance as needed throughout the implementation process. Future directions include enhancing the platform for use in teaching real-time imaging processing techniques such as histograms, profiles, projections, filtering and edge detection and using a virtual voice assistant for each image processing operation.
AU  - Sheng-jen Hsieh
CY  - Minneapolis, MN
DA  - 2022/08/23
PB  - ASEE Conferences
TI  - Remote Machine Vision Lab Design and Evaluation using AI based Mobile Robot
UR  - https://peer.asee.org/40587
DO  - 10.18260/1-2--40587
ER  -