TY - GEN
T1 - Motor Imitation
T2 - 2022 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)
AU - Jouaiti, Melanie
N1 - Presented 30 May 2022 at IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)
PY - 2022/6/27
Y1 - 2022/6/27
N2 - Achieving pose imitation with robots is a quite popular topic in robotics. It is widely used for children therapy, notably autistic children, but also to teach new actions to robots. While a lot of very effective methods exist for pose imitation, most of these rely on supplementary equipment for motion capture which rule out a natural interaction and even prevent an interaction which could take place outside of the laboratory.In this paper, we propose a bio-inspired method to achieve imitation with minimal equipment, relying solely on the information provided by the robot Pepper 2D camera. To do so, we perform 2D pose estimation using OpenPose to infer the 3D pose estimation of the human. Using this information, we performed rhythmic and discrete pose imitation using CPG (Central Pattern Generators) controllers endowed with plasticity mechanisms and compared this method with a geometric control approach. Although CPG control has been used previously for rhythmic tasks, it has never been, to our knowledge, been used for imitation.
AB - Achieving pose imitation with robots is a quite popular topic in robotics. It is widely used for children therapy, notably autistic children, but also to teach new actions to robots. While a lot of very effective methods exist for pose imitation, most of these rely on supplementary equipment for motion capture which rule out a natural interaction and even prevent an interaction which could take place outside of the laboratory.In this paper, we propose a bio-inspired method to achieve imitation with minimal equipment, relying solely on the information provided by the robot Pepper 2D camera. To do so, we perform 2D pose estimation using OpenPose to infer the 3D pose estimation of the human. Using this information, we performed rhythmic and discrete pose imitation using CPG (Central Pattern Generators) controllers endowed with plasticity mechanisms and compared this method with a geometric control approach. Although CPG control has been used previously for rhythmic tasks, it has never been, to our knowledge, been used for imitation.
KW - Three-dimensional displays
KW - Conferences
KW - Pose estimation
KW - Robot vision systems
KW - Medical treatment
KW - Cameras
KW - Generators
U2 - 10.1109/ARSO54254.2022.9802963
DO - 10.1109/ARSO54254.2022.9802963
M3 - Conference contribution
SN - 9781665483520
T3 - IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO
SP - 1
EP - 6
BT - 2022 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)
PB - IEEE
Y2 - 28 May 2022 through 30 May 2022
ER -