TY - GEN
T1 - Proficiency based planner for safe path planning and applications in surgical training
AU - Jain, Shubham
AU - Hong, Minsik
AU - Rozenblit, Jerzy W.
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under Grant Number 1622589 Computer Guided Laparoscopy Training. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Funding Information:
This material is based upon work supported by the National Science Foundation under Grant Number 1622589 “Computer Guided Laparoscopy Training”. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
© 2019 SCS.
PY - 2019/4
Y1 - 2019/4
N2 - Instrument navigation is a fundamental task in laparoscopic surgical training. To assist a trainee in this task, suggested path needs to be collision free and should maintain sufficient distance, or clearance from the obstacle so that the possibility of collision is minimized. Clearance highly depends on the ability of a trainee to perform the task. In this paper, we propose a new algorithm for suggesting a path for a navigation task, that considers Proficiency Level of the trainee and provides a path according to how well a trainee can perform. The suggested approach is based on Probabilistic Roadmap Planners (PRM) and focuses on certain configuration spaces where most planners may fail to find a path while guaranteeing path's clearance. The new method provides a way to compensate for clearance constraints in regions wherever such compensation is necessary. Finally, the simulation in a surgical trainer demonstrates the effectiveness of the method.
AB - Instrument navigation is a fundamental task in laparoscopic surgical training. To assist a trainee in this task, suggested path needs to be collision free and should maintain sufficient distance, or clearance from the obstacle so that the possibility of collision is minimized. Clearance highly depends on the ability of a trainee to perform the task. In this paper, we propose a new algorithm for suggesting a path for a navigation task, that considers Proficiency Level of the trainee and provides a path according to how well a trainee can perform. The suggested approach is based on Probabilistic Roadmap Planners (PRM) and focuses on certain configuration spaces where most planners may fail to find a path while guaranteeing path's clearance. The new method provides a way to compensate for clearance constraints in regions wherever such compensation is necessary. Finally, the simulation in a surgical trainer demonstrates the effectiveness of the method.
KW - Laparoscopic training
KW - Path repairing
KW - Probabilistic roadmap planners
KW - Safe path planning
UR - http://www.scopus.com/inward/record.url?scp=85068621313&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068621313&partnerID=8YFLogxK
U2 - 10.23919/SpringSim.2019.8732852
DO - 10.23919/SpringSim.2019.8732852
M3 - Conference contribution
AN - SCOPUS:85073695876
T3 - 2019 Spring Simulation Conference, SpringSim 2019
BT - 2019 Spring Simulation Conference, SpringSim 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Spring Simulation Conference, SpringSim 2019
Y2 - 29 April 2019 through 2 May 2019
ER -