Person:

Lock, Jesse

A novel approach to constructing robots is based on concentrically combining pre-curved elastic tubes. By rotating and extending the tubes with respect to each other, their curvatures interact elastically to position and orient the robot's tip, as well as to control the robot's shape along its length. Since these robots form slender curves, they are well suited for minimally invasive medical procedures. A substantial challenge to their practical use is the real-time solution of their kinematics that are described by differential equations with split boundary equations. This paper proposes a numerically efficient approach to real-time position control. It is shown that the forward kinematics are smooth functions that can be pre-computed and accurately approximated using Fourier series. The inverse kinematics can be solved in real time using root finding applied to the functional approximation. Experimental demonstration of real-time position control using this approach is also described.

Surgical robots are gaining favor in part due to their capacity to reach remote locations within the body. Continuum robots are especially well suited for accessing deep spaces such as cerebral ventricles within the brain. Due to the entry point constraints and complicated structure, current techniques do not allow surgeons to access the full volume of the ventricles. The ability to access the ventricles with a dexterous robot would have significant clinical implications. This paper presents a concentric tube manipulator mated to a robotically controlled flexible endoscope. The device adds three degrees of freedom to the standard neuroendoscope and roboticizes the entire package allowing the operator to conveniently manipulate the device. To demonstrate the improved functionality, we use an in-silica virtual model as well as an ex-vivo anatomic model of a patient with a treatable form of hydrocephalus. In these experiments we demonstrate that the augmented and roboticized endoscope can efficiently reach critical regions that a manual scope cannot.

Concentric tube robots are a novel class of continuum robots that are constructed by combining pre-curved elastic tubes such that the overall shape of the robot is a function of the relative rotations and translations of the constituent tubes. Frictionless kinematic and quasistatic force models for this class of robots have been developed that incorporate bending and twisting of the tubes. Experimental evaluation of these models has revealed, however, a directional dependence of tube rotation on robot shape that is not predicted by these models. To explain this behavior, this paper models the contributions of friction arising from two sources: the distributed forces of contact between the tubes along their length and the concentrated bending moments generated at discontinuities in curvature and at the boundaries. It is shown that while friction due to distributed forces is insufficient to explain the experimentally observed tube twisting, a simple model of frictional torque arising from concentrated moments provides a good match with the experimental data.

Concentric tube robots are a subset of continuum robots constructed by combining pre-curved elastic tubes. As the tubes are rotated and translated with respect to each other, their curvatures interact elastically, enabling control of the robot's tip configuration as well as the curvature along its length. This technology is projected to be useful in many types of minimally invasive medical procedures. Because these robots are flexible by design, they deflect considerably when applying forces to the external environment. Thus, in contrast to rigid-link robots, their kinematic and static force models are coupled. This paper derives a multi-tube quasistatic model that relates tube rotations and translations together with externally applied loads to robot shape and tip configuration. The model can be applied in robot design, procedure planning as well as control. For validation, the multi-tube model is compared experimentally to a computationally-efficient single-tube approximate model.