Auto-tracker characterization with robotics applications
Computing devices and methods are provided to automatically characterize a localization system tracker for a procedure. A starting tracker definition is refined until convergence using an iterative process and measured features of the tracker in images provided by a localization system camera. In each iteration, poses are determined from the measured features using a current tracker definition. The current definition is then refined using the poses and an optimization function. Tracker images may be captured passively, when performing other procedure steps. In a robotic context, command trajectories move a robot may be to respective poses where images to characterize the tracker are captured. An updated trajectory may be commanded to optimize convergence, additionally using the measured features at the updated pose in the iterative process. A robot kinematic model may be defined, refining a starting model using tracker poses from the localization system and sensor positions from the robot system.
1. A method to perform tracker characterization, the method comprising:
receiving, at a processing unit from a camera of a localization system, a plurality of images of a tracker, wherein the images include a plurality of measured tracker features with which to characterize the tracker and wherein a baseline tracker definition, accessible to the processing unit, specifies baseline tracker features to characterize the tracker;
determining a second tracker definition for the tracker using the measured tracker features in accordance with an iterative process to refine the second tracker definition in successive current iterations of the iterative process, each of the successive current iterations: calculating current poses of the tracker using the measured tracker features and a current instance of the second tracker definition; and refining the current instance of the second tracker definition using the current poses; and
using the second tracker definition in the performance of a procedure.
2. The method of claim 1 , wherein the plurality of images are generated by the camera during a use of the tracker to collect data for the procedure other than to perform tracker characterization.
3. The method of claim 2 , wherein the use of the tracker to collect data comprises any one or more of:
performing a registration using the tracker;
performing a baseline measure of a patient anatomy; or
performing workflow of the procedure to determine a clinical measurement.
4. The method of claim 1 , wherein determining the second tracker definition comprises:
iteratively, for each current instance of the iterative process:
respectively processing the plurality of images to determine the current poses of the tracker in each of the images; and
refining the second tracker definition using a tracker defining optimization process responsive to the current poses and the current instance of the second tracker definition, the optimization process using the baseline tracker definition in a first iteration.
5. The method of claim 4 , wherein the tracker defining optimization process comprises a gradient descent optimization process.
6. The method of claim 4 , wherein respectively processing the plurality of images to determine the current poses uses a pose defining optimization process.
7. The method of claim 4 , wherein the second tracker definition is iteratively refined in accordance with either 1) a predetermined count of iterations; or 2) a convergence test where the second tracker definition is within a threshold of a previous iteration of the second tracker definition.
8. The method of claim 4 comprising scaling the second tracker definition at each iteration to have a similar scale parameter to a pre-set scale.
9. The method of claim 1 , wherein the step of determining the second tracker definition is performed in a background manner, without interrupting a workflow of the procedure.
10. The method of claim 1 , wherein using the second tracker definition comprises determining whether or not to perform further steps of the procedure.
11. The method of claim 1 comprising:
computing a tracker assessment parameter comparing the second tracker definition and first tracker definition and, at least one of:
displaying the tracker assessment parameter numerically or graphically;
providing a warning; and
stopping performing the procedure.
12. The method of claim 1 comprising verifying that the plurality of images represent the tracker from a different number of angles to accurately characterize the tracker; and collecting at least one additional image for the plurality of images.
13. The method of claim 12 comprising calculating an angular coverage measure using the plurality of images.
14. The method of claim 1 , wherein the tracker features comprise a plurality of markers, wherein the baseline tracker definition is responsive to a baseline configuration of the plurality of markers.
15. The method of claim 1 , wherein the method is performed by a trajectory planner component of a robotic system.
16. A method to perform tracker characterization, the method comprising:
determining, at a processing unit, and communicating a plurality of respective trajectories to command movement of a robot to respective poses, the robot comprising a plurality of connected linkages and an effector at a distal end of the connected linkages, one of the linkages coupled to either a camera or a tracker of a localization system and wherein an object has coupled thereto the other of the camera and the tracker;
receiving, at the processing unit from the camera, respective images of the tracker for each of the respective poses of the robot, each of the respective images comprising a plurality of measured tracker features with which to characterize the tracker and wherein a baseline tracker definition, accessible to the processing unit, specifies baseline tracker features to characterize the tracker;
determining a second tracker definition for the tracker using the measured tracker features in accordance with an iterative process to refine the second tracker definition in successive current iterations of the iterative process, wherein each of the successive current iterations: calculates current poses in the respective images of the tracker using the measured tracker features and a current tracker definition; and refines the current tracker definition using the current poses in accordance with an optimization function; and
using the second tracker definition in the performance of a procedure.
17. The method of claim 16 , wherein the iterative process refines the second tracker definition through a convergence such that further iterations fail to provide an improvement in the second tracker definition or where any improvement is below a threshold of significance.
18. The method of claim 17 comprising:
determining and communicating an updated trajectory to the robot to command movement to an updated pose to optimize the convergence;
receiving an updated image comprising measured features of the tracker relative to the updated pose; and
additionally using the measured features of the updated image when calculating the current poses and when refining the second tracker definition.
19. The method of claim 18 comprising calculating a direction of maximal uncertainty and using the maximal uncertainty to determine the updated trajectory.
20. The method of claim 18 , wherein the respective trajectories and the updated trajectory are calculated to avoid obstacles and robot singularities.
21. The method of claim 18 comprising optimizing a time to complete the tracker characterization, defining the respective trajectories and the updated trajectory in response to robot dynamics and kinematics to command movement of the robot to the respective poses and the updated pose which minimizes a time taken to move the robot linkages.
22. The method of claim 16 comprising determining a directional uncertainty.