Methods and system for performing 3-D tool tracking by fusion of sensor and/or camera derived data during minimally invasive robotic surgery
Methods and system perform tool tracking during minimally invasive robotic surgery. Tool states are determined using triangulation techniques or a Bayesian filter from either or both non-endoscopically derived and endoscopically derived tool state information, or from either or both non-visually derived and visually derived tool state information. The non-endoscopically derived tool state information is derived from sensor data provided either by sensors associated with a mechanism for manipulating the tool, or sensors capable of detecting identifiable signals emanating or reflecting from the tool and indicative of its position, or external cameras viewing an end of the tool extending out of the body. The endoscopically derived tool state information is derived from image data provided by an endoscope inserted in the body so as to view the tool.
1. A tool tracking method comprising:
determining a first estimated tool state relative to a landmark for a point in time using first sensor data indicative of the tool state at the point in time;
determining an estimated camera state relative to the landmark for the point in time using second sensor data indicative of the camera state at the point in time;
determining a second estimated tool state relative to the camera for the point in time using image data generated by the camera and indicative of the tool state at the point in time;
translating the first estimated tool state so as to be relative to the camera instead of the landmark; and
computing an error transform between the translated first and the second estimated tool states so that at a subsequent point in time if image data indicative of the tool state at the subsequent point in time is not available, then the tool state is determined by applying the error transform to a third estimated tool state determined using sensor data indicative of the tool state at the subsequent point in time translated so as to be relative to the camera instead of the landmark.
2. The method according to claim 1 , further comprising if the image data indicative of the tool state at the subsequent point in time is available: determining a fourth estimated tool state relative to the camera for the subsequent point in time using image data generated by the camera and indicative of the tool state at the subsequent point in time; and determining the tool state at the subsequent point in time as being the fourth estimated tool state.
3. The method according to claim 2 , further comprising if the image data indicative of the tool state at the subsequent point in time is available: computing a second error transform between the translated third and the fourth estimated tool states so that at a subsequent, subsequent point in time if image data indicative of the tool state at the subsequent, subsequent point in time is not available, then the tool state is determined by applying the second error transform to a fifth estimated tool state determined using sensor data indicative of the tool state at the subsequent, subsequent point in time translated so as to be relative to the camera instead of the landmark.
4. A medical system comprising:
a tool;
a first sensor, the first sensor adapted to generate first sensor data indicative of a state of the tool at a point in time;
an image capture device, the image capture device disposed so as to generate image data indicative of the state of the tool at the point in time;
a second sensor, the second sensor adapted to generate second sensor data indicative of a state of the image capture device at the point in time; and
a processor programmed to:
determine a first estimated tool state relative to a landmark for the point in time using the first sensor data;
determine an estimated image capture device state relative to the landmark for the point in time using the second sensor data;
determine a second estimated tool state relative to the image capture device for the point in time using the image data;
translating the first estimated tool state so as to be relative to the image capture device instead of the landmark; and
computing an error transform between the translated first and the second estimated tool states so that at a subsequent point in time if image data indicative of the tool state at the subsequent point in time is not available, then the tool state is determined by applying the error transform to a third estimated tool state determined using sensor data indicative of the tool state at the subsequent point in time translated so as to be relative to the image capture device instead of the landmark.
5. The medical system according to claim 4 ,
wherein the processor is further programmed to:
conditioned upon the image data indicative of the tool state at the subsequent point in time being available,
determine a fourth estimated tool state relative to the image capture device for the subsequent point in time using image data generated by the image capture device and indicative of the tool state at the subsequent point in time; and
determine the tool state at the subsequent point in time as being the fourth estimated tool state.
6. The medical system according to claim 5 ,
wherein the processor is further programmed to:
conditioned upon the image data indicative of the tool state at the subsequent point in time being available,
computing a second error transform between the translated third and the fourth estimated tool states so that at a subsequent, subsequent point in time if image data indicative of the tool state at the subsequent, subsequent point in time is not available, then the tool state is determined by applying the second error transform to a fifth estimated tool state determined using sensor data indicative of the tool state at the subsequent, subsequent point in time translated so as to be relative to the image capture device instead of the landmark.