Motion Planning for Concentric Tube Robots

Concentric tube robot

We explore motion planning for concentric tube robots, new tentacle-like medical devices composed of thin, pre-curved, telescoping tubes. These devices can follow curved, winding paths through open cavities and soft tissues to reach distant targets in constrained spaces, enabling minimally-invasive access to previously unreachable sites. As part of a inter-university NIH-supported collaboration, we are investigating using concentric tube robots in skull base surgery to access the pituitary gland and nearby brain structures via the nasal cavity. The tentacle-like abilities of these devices could enable steering around obstacles such as the carotid arteries and critical brain tissue to complete challenging surgical procedures.

Concentric tube robots can be controlled by axially rotating and/or telescopically translating individual tubes, which modifies the curvilinear shape of the device as the nested tubes elastically interact. Controlling tube axial rotations and translations to achieve a desired curvilinear shape or tip pose is unintuitive for humans, motivating the need for new user interfaces and efficient planning algorithms.

Concentric tube robot for skull base surgery

Reaching Targets: We are developing new motion planners to automatically maneuver concentric tube robots to physician-specified clinical targets while avoiding collision with anatomical obstacles. A key challenge is that changing the pose of the device's tip necessarily induces a change in the shape of the entire shaft due to tube bending and torsional interactions. Our latest motion planners estimate device shape using mechanics-based models that consider torsional interaction between the tubes, which requires solving a numerical system for each robot configuration. We are also developing methods that account for the effects of uncertainty in predicted device shape due to uncertainty in tube torsion and frictional parameters. We are also developing algorithms for estimating the shape of the concentric robot continuously over the course of a procedure using a minimal number of 2D sensor views by integrating stochastic models of device shape.

Task-oriented Robot Design: Optimizing the design of the tubes of a concentric tube robot on a patient-specific and procedure-specific basis has the potential to enable access to even more challenging sites inside the body. The design parameters include the lengths and precurvatures of the robot’s constituent tubes, which must be set before the procedure. We are developing methods that combine a search over a robot’s design parameters with sampling-based motion planning over its configuration space to compute a design under which the robot can feasibly perform a specified task without damaging surrounding tissues.

Interactive Motion Planning: Concentric tube robots can do more than reach a target in constrained anatomy; they also can manipulate tissues at the target when mounted with end effectors such as micro-scale grippers and cauterizers. Motion planning can enable physicians to continuously specify the end effector pose while the motion planner repeatedly executes with high frequency to ensure that the entire curvilinear shaft avoids obstacles. We are using precomputation and parallelization to achieve fast, interactive performance.

This research is in collaboration with the MEDLab at Vanderbilt University as well as physicians at Vanderbilt University and UNC-Chapel Hill.

Collaborators

Publications/Presentations

  1. Cenk Baykal and Ron Alterovitz, "Asymptotically Optimal Design of Piecewise Cylindrical Robots using Motion Planning," in Proc. Robotics: Science and Systems (RSS), July 2017, pp. 1-10. (Publisher) (Download PDF)
    (Best Paper Award)
  2. Alan Kuntz, Philip J. Swaney, Arthur W. Mahoney, Richard H. Feins, Yueh Z. Lee, Robert J. Webster III, and Ron Alterovitz, "Toward Transoral Peripheral Lung Access: Steering Bronchoscope-deployed Needles through Porcine Lung Tissue," in Hamlyn Symposium on Medical Robotics, June 2016. (Download PDF)
  3. Alan Kuntz, Luis G. Torres, Richard H. Feins, Robert J. Webster III, and Ron Alterovitz, "Motion Planning for a Three-Stage Multilumen Transoral Lung Access System," in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sep. 2015, pp. 3255-3261. (Publisher) (Download PDF)
  4. Cenk Baykal, Luis G. Torres, and Ron Alterovitz, "Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning," in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sep. 2015, pp. 4381-4387. (Publisher) (Download PDF)
  5. Philip J. Swaney, Hunter B. Gilbert, Richard J. Hendrick, Oliver Commichau, Ron Alterovitz, Robert J. Webster III, "Transoral Steerable Needles in the Lung: How Non-annular Concentric Tube Robots Can Improve Targeting," in Hamlyn Symposium on Medical Robotics, June 2015, pp. 37-38. (Download PDF)
    (Best Oral Presentation)
  6. Luis G. Torres, Alan Kuntz, Hunter B. Gilbert, Philip J. Swaney, Richard J. Hendrick, Robert J. Webster III, and Ron Alterovitz, "A Motion Planning Approach to Automatic Obstacle Avoidance during Concentric Tube Robot Teleoperation," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2015, pp. 2361-2367. (Publisher) (Download PDF)
  7. Philip J. Swaney, Arthur W. Mahoney, Andria A. Remirez, Erik Lamers, Bryan I. Hartley, Richard H. Feins, Ron Alterovitz, and Robert J. Webster III, "Tendons, Concentric Tubes, and a Bevel Tip: Three Steerable Robots in One Transoral Lung Access System," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2015, pp. 5378-5383. (Publisher) (Download PDF)
  8. Luis G. Torres, Cenk Baykal, and Ron Alterovitz, "Interactive-rate Motion Planning for Concentric Tube Robots," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2014, pp. 1915-1921. (Publisher) (Download PDF)
  9. Raul Wirz, Luis G. Torres, Philip J. Swaney, Hunter Gilbert, Ron Alterovitz, Robert J. Webster III, Kyle D. Weaver, and Paul T. Russell III, "An Experimental Feasibility Study on Robotic Endonasal Telesurgery," Neurosurgery, vol. 76, no. 4, pp. 479-484, Apr. 2015. (Publisher)
  10. Wen Sun, Luis G. Torres, Jur van den Berg, and Ron Alterovitz, "Safe Motion Planning for Imprecise Robotic Manipulators by Minimizing Probability of Collision," in Proc. International Symposium on Robotics Research (ISRR), Dec. 2013. (Download PDF)
  11. Edgar J. Lobaton, Jinghua Fu, Luis G. Torres, and Ron Alterovitz, "Continuous Shape Estimation of Continuum Robots Using X-ray Images," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2013, pp. 717-724. (Publisher) (Download PDF)
  12. Luis G. Torres, Robert J. Webster III, and Ron Alterovitz, "Task-oriented Design of Concentric Tube Robots using Mechanics-based Models," in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2012, pp. 4449-4455. (Publisher) (Download PDF)
  13. Luis G. Torres and Ron Alterovitz, "Motion Planning for Concentric Tube Robots Using Mechanics-based Models," in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sept. 2011, pp. 5153-5159. (Publisher) (Download PDF)
  14. Ron Alterovitz, Sachin Patil, and Anna Derbakova, "Rapidly-Exploring Roadmaps: Weighing Exploration vs. Refinement in Optimal Motion Planning," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2011, pp. 3706-3712. (Publisher) (Download PDF)
  15. Lisa A. Lyons, Robert J. Webster III, and Ron Alterovitz, "Planning Active Cannula Configurations Through Tubular Anatomy," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2010, pp. 2082-2087. (Publisher) (Download PDF)
  16. Lisa A. Lyons, Robert J. Webster III, and Ron Alterovitz, "Motion Planning for Active Cannulas," in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2009, pp. 801-806. (Publisher) (Download PDF)

This research is made possible by generous support from the National Science Foundation (NSF) under awards IIS-0905344 and IIS-1149965 and by the National Institutes of Health (NIH) under awards R21EB011628, R01EB017467, R21EB017952, and R01EB024864. Any opinions, findings, and conclusions or recommendations expressed on this web site do not necessarily reflect the views of NSF or NIH.