TY - GEN
T1 - Human-machine interface for remote training of robot tasks
AU - Spranger, Jordi Jeremi Robert Rhett
AU - Buzatoiu, Roxana
AU - Polydoros, Athanasios
AU - Nalpantidis, Lazaros
AU - Boukas, Evangelos
PY - 2018/12/14
Y1 - 2018/12/14
N2 - Regardless of their industrial or research application, the streamlining of robot operations is limited by the proximity of experienced users to the actual hardware. Be it massive open online robotics courses, crowd-sourcing of robot task training, or remote research on massive robot farms for machine learning, the need to create an apt remote Human-Machine Interface is quite prevalent. The paper at hand proposes a novel solution to the programming/training of remote robots employing an intuitive and accurate user-interface which offers all the benefits of working with real robots without imposing delays and inefficiency. The system includes: A vision-based 3D hand detection and gesture recognition subsystem, a simulated digital twin of a robot as visual feedback, and the 'remote' robot learning/executing trajectories using dynamic motion primitives. Our results indicate that the system is a promising solution to the problem of remote training of robot tasks.
AB - Regardless of their industrial or research application, the streamlining of robot operations is limited by the proximity of experienced users to the actual hardware. Be it massive open online robotics courses, crowd-sourcing of robot task training, or remote research on massive robot farms for machine learning, the need to create an apt remote Human-Machine Interface is quite prevalent. The paper at hand proposes a novel solution to the programming/training of remote robots employing an intuitive and accurate user-interface which offers all the benefits of working with real robots without imposing delays and inefficiency. The system includes: A vision-based 3D hand detection and gesture recognition subsystem, a simulated digital twin of a robot as visual feedback, and the 'remote' robot learning/executing trajectories using dynamic motion primitives. Our results indicate that the system is a promising solution to the problem of remote training of robot tasks.
KW - Dynamic Motion Primitives
KW - Hand Detection
KW - Human-Machine Interface
KW - Remote Robots
KW - Remote Training
KW - Robot Tasks
UR - http://www.scopus.com/inward/record.url?scp=85060688590&partnerID=8YFLogxK
U2 - 10.1109/IST.2018.8577081
DO - 10.1109/IST.2018.8577081
M3 - Article in proceeding
AN - SCOPUS:85060688590
T3 - IEEE International Conference on Imaging Systems and Techniques (IST)
BT - IST 2018 - IEEE International Conference on Imaging Systems and Techniques, Proceedings
PB - IEEE
T2 - 2018 IEEE International Conference on Imaging Systems and Techniques, IST 2018
Y2 - 16 October 2018 through 18 October 2018
ER -