TY - GEN
T1 - Autonomous Field-of-View Adjustment Using Adaptive Kinematic Constrained Control with Robot-Held Microscopic Camera Feedback
AU - Lin, Hung Ching
AU - Marinho, Murilo Marques
AU - Harada, Kanako
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/8/8
Y1 - 2024/8/8
N2 - Robotic systems for manipulation in millimeter scale often use a camera with high magnification for visual feedback of the target region. However, the limited field-of-view (FoV) of the microscopic camera necessitates camera motion to capture a broader workspace environment. In this work, we propose an autonomous robotic control method to constrain a robot-held camera within a designated FoV. Furthermore, we model the camera extrinsics as part of the kinematic model and use camera measurements coupled with a U-Net based tool tracking to adapt the complete robotic model during task execution. As a proof-of-concept demonstration, the proposed framework was evaluated in a bi-manual setup, where the microscopic camera was controlled to view a tool moving in a pre-defined trajectory. The proposed method allowed the camera to stay 94.1% of the time within the real FoV, compared to 54.4% without the proposed adaptive control.
AB - Robotic systems for manipulation in millimeter scale often use a camera with high magnification for visual feedback of the target region. However, the limited field-of-view (FoV) of the microscopic camera necessitates camera motion to capture a broader workspace environment. In this work, we propose an autonomous robotic control method to constrain a robot-held camera within a designated FoV. Furthermore, we model the camera extrinsics as part of the kinematic model and use camera measurements coupled with a U-Net based tool tracking to adapt the complete robotic model during task execution. As a proof-of-concept demonstration, the proposed framework was evaluated in a bi-manual setup, where the microscopic camera was controlled to view a tool moving in a pre-defined trajectory. The proposed method allowed the camera to stay 94.1% of the time within the real FoV, compared to 54.4% without the proposed adaptive control.
UR - http://www.scopus.com/inward/record.url?scp=85202433733&partnerID=8YFLogxK
U2 - 10.1109/ICRA57147.2024.10610663
DO - 10.1109/ICRA57147.2024.10610663
M3 - Conference contribution
AN - SCOPUS:85202433733
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 2162
EP - 2168
BT - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PB - IEEE
T2 - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Y2 - 13 May 2024 through 17 May 2024
ER -