TY - GEN
T1 - Virtual Reality Application for Co-Bot Training
AU - Haz, Amma Liesvarastranta
AU - Muhtadin,
AU - Ketut Eddy Purnama, I.
AU - Purnomo, Mauridhi Hery
AU - Sukaridhoto, Sritrusta
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The direction of robot technology development is now towards human-centric robots where co-bots are starting to be in demand as assistants for human work. Working together means needing to get used to each other's behavior so as to create collaborative interactions between each other. To create that sense of familiarity, Co-Bot Interaction Virtual Training (CBIVT) was developed. CBIVT is used in wireless all-in-one VR devices thereby increasing user-friendliness. As a simulation scenario of the interaction between the Co-Bot and the user, the furniture assembly procedure was chosen. And, with the help of the path finding algorithm, the behavior of the Co-Bot AI to follow and approach the user is also created. To assess the importance and satisfaction of CBIVT, 32 participants were assigned to complete scenarios and then complete a questionnaire. Using the PIECES framework to assess the above parameters, we get results of 3.95 out of 5 for importance level and 3.99 out of 5 for satisfaction level.
AB - The direction of robot technology development is now towards human-centric robots where co-bots are starting to be in demand as assistants for human work. Working together means needing to get used to each other's behavior so as to create collaborative interactions between each other. To create that sense of familiarity, Co-Bot Interaction Virtual Training (CBIVT) was developed. CBIVT is used in wireless all-in-one VR devices thereby increasing user-friendliness. As a simulation scenario of the interaction between the Co-Bot and the user, the furniture assembly procedure was chosen. And, with the help of the path finding algorithm, the behavior of the Co-Bot AI to follow and approach the user is also created. To assess the importance and satisfaction of CBIVT, 32 participants were assigned to complete scenarios and then complete a questionnaire. Using the PIECES framework to assess the above parameters, we get results of 3.95 out of 5 for importance level and 3.99 out of 5 for satisfaction level.
KW - Collaborative Robot
KW - Human Computer Interaction
KW - Serious Game
KW - Virtual Reality
UR - http://www.scopus.com/inward/record.url?scp=85139630265&partnerID=8YFLogxK
U2 - 10.1109/IES55876.2022.9888286
DO - 10.1109/IES55876.2022.9888286
M3 - Conference contribution
AN - SCOPUS:85139630265
T3 - IES 2022 - 2022 International Electronics Symposium: Energy Development for Climate Change Solution and Clean Energy Transition, Proceeding
SP - 644
EP - 650
BT - IES 2022 - 2022 International Electronics Symposium
A2 - Yunanto, Andhik Ampuh
A2 - Prayogi, Yanuar Risah
A2 - Putra, Putu Agus Mahadi
A2 - Hermawan, Hendhi
A2 - Nailussa'ada, Nailussa'ada
A2 - Ruswiansari, Maretha
A2 - Ridwan, Mohamad
A2 - Gamar, Farida
A2 - Ramadhani, Afifah Dwi
A2 - Rahmawati, Weny Mistarika
A2 - Rusli, Muhammad Rizani
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th International Electronics Symposium, IES 2022
Y2 - 9 August 2022 through 11 August 2022
ER -
