TY - GEN
T1 - Autonomous Data-Driven Manipulation of an Unknown Deformable Tissue Within Constrained Environments
T2 - 2022 International Symposium on Medical Robotics, ISMR 2022
AU - Retana, Manuel
AU - Nalamwar, Kunal
AU - Conyers, Drew T.
AU - Atashzar, S. Farokh
AU - Alambeigi, Farshid
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - To ensure safety and precision of autonomous surgical tasks performed on deformable tissues (DTs), in this paper, we propose a model-independent constrained optimization framework that is able to simultaneously learn deformation behavior of an unknown DT while autonomously manipulating it within a constrained and confined environment. To thoroughly evaluate the performance of the proposed framework, we used the da Vinci Research Kit and performed various experiments on an unknown DT phantom. We particularly compared the performance of our algorithm in 10 different configurations with and without the presence of imposed virtual workspace constraints. Results demonstrated the successful performance of the proposed framework in online deformation learning and manipulation of an unknown DT and revealed the effects of imposing constraints on the proposed model-independent framework.
AB - To ensure safety and precision of autonomous surgical tasks performed on deformable tissues (DTs), in this paper, we propose a model-independent constrained optimization framework that is able to simultaneously learn deformation behavior of an unknown DT while autonomously manipulating it within a constrained and confined environment. To thoroughly evaluate the performance of the proposed framework, we used the da Vinci Research Kit and performed various experiments on an unknown DT phantom. We particularly compared the performance of our algorithm in 10 different configurations with and without the presence of imposed virtual workspace constraints. Results demonstrated the successful performance of the proposed framework in online deformation learning and manipulation of an unknown DT and revealed the effects of imposing constraints on the proposed model-independent framework.
UR - http://www.scopus.com/inward/record.url?scp=85134390623&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134390623&partnerID=8YFLogxK
U2 - 10.1109/ISMR48347.2022.9807519
DO - 10.1109/ISMR48347.2022.9807519
M3 - Conference contribution
AN - SCOPUS:85134390623
T3 - 2022 International Symposium on Medical Robotics, ISMR 2022
BT - 2022 International Symposium on Medical Robotics, ISMR 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 13 April 2022 through 15 April 2022
ER -