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Motion Planning for Concentric Tube Robots
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. In a concentric tube robot, bending actuation arises as tubes elastically interact when they slide and rotate within one another. Planning tube configurations (translations and axial rotations applied at tube bases) that correspond to desired spatial tip coordinates or shaft curves is not intuitive for human beings, motivating the need for efficient planning algorithms. We are developing new motion planners to maneuver these devices to clinical targets while minimizing the probability of colliding with anatomical obstacles. Our latest algorithms accurately model device shape using mechanics-based models that consider torsional interaction between the tubes and account for the effects of uncertainty in predicted device shape. We integrate these models with a new sampling-based approach called the Rapidly Exploring Roadmap to guarantee finding optimal plans as computation time is allowed to increase. We demonstrate our motion planner in simulation using a variety of evaluation scenarios including an anatomy-based neurosurgery case that requires maneuvering to a difficult-to-reach brain tumor at the skull base. This research is in collaboration with the MEDLab at Vanderbilt University. Publications/Presentations
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