ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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S&M2172 Research Paper of Special Issue

Asymmetric Bimanual Control of Dual-arm Serial Manipulator for Robot-assisted Minimally Invasive Surgeries

Hang Su, Yunus Schmirander, Sarah Elena Valderrama-Hincapie, Jairo Pinedo, Xuanyi Zhou, Jiehao Li, Longbin Zhang, Yingbai Hu, Giancarlo Ferrigno, and Elena De Momi

(Received September 13, 2019; Accepted February 20, 2020)

Keywords: bimanual control, minimally invasive surgery, radial basis function neural network, redundant manipulator, remote center of motion

Robotic assistance is promising for improving minimally invasive surgery (MIS). This work presents asymmetric bimanual control of a dual-arm serial robot with two remote centers of motion (RCMs) constraints for MIS. In our previous works, general null space controllers to guarantee the fixed RCM constraint have been proposed. However, an incision on a patient’s abdominal wall is not fixed owing to the respiration of the patient, which generates an uncertain disturbance at the joints of robotic manipulators. To improve accuracy, a radial basis function neural network is implemented to adapt to these disturbances and control the end-effector position. Finally, the adaptive bimanual control strategy is validated through simulations based on clinical data. The proposed control shows improved accuracy in the end effector position for all the designed surgical tasks. In future works, the algorithm will be validated on an actual dual-arm serial robot making use of a body phantom.

Corresponding author: Yingbai Hu




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