Concurrent nonparametric estimation of organ geometry and tissue stiffness using continuous adaptive palpation

摘要

Surgeons often manually palpate tissue or organs in order to find tumors or other anatomical structures. Information about organ geometry and tissue stiffness gained from palpation can also be extremely useful in robotic surgery for diagnosis, surgical guidance, and registration to other preoperative information. However, it is not always easy to obtain, even if the robot is equipped with force sensors. This paper reports our approach for concurrent estimation of stiffness and surface geometry, using a continuous motion similar to a sweeping palpation motion used by surgeons. Our method relies on force data captured by a tactile sensor rigidly attached to an end-effector probe. We use Gaussian processes to simultaneously estimate geometry and stiffness. The method is not tied to any specific robotic platform and is consistent with a variety of palpation strategies. For simplicity, we discuss the results based on two different palpation primitives. This is our first step towards developing an adaptive high fidelity model reconstruction and path optimization technique.