Abstract: In some examples, one or more processors of an aerial vehicle determine an update to a three-dimensional (3D) model corresponding to a scan target to scan according to a scan plan. Based at least on the update to the 3D model, the one or more processors determine a set of one or more uncovered points of the 3D model that are not covered by the scan plan. Additionally, the one or more processors determine an updated scan plan based at least on determining one or more poses to include in the scan plan for scanning the one or more uncovered points of the 3D model. The one or more processors, control the aerial vehicle to scan the scan target with the one or more image sensors according to the updated scan plan.

Abstract: In some examples, one or more processors of an unmanned aerial vehicle (UAV), control a propulsion mechanism of the UAV to cause the UAV to navigate to a plurality of positions in relation to a scan target. Using one or more image sensors of the UAV, a first image of the scan target is captured from a first position of the plurality of positions, and a second image of the scan target is captured from a second position of the plurality of positions. A disparity is determined between the first image captured at the first position and the second image captured at the second position. A three-dimensional model corresponding to the scan target is determined based in part on the disparity determined between the first image and the second image.

Abstract: In some examples, one or more processors of an aerial vehicle access a scan plan including a sequence of poses for the aerial vehicle to assume to capture, using the one or more image sensors, images of a scan target. A next pose of the scan plan is checked for obstructions, and based at least on detection of an obstruction, the one or more processors determine whether a backup pose is available for capturing an image of the targeted point orthogonally along a normal of the targeted point. Responsive to determining that the backup pose is unavailable for capturing an image of the targeted point orthogonally along the normal of the targeted point, image capture of the targeted point is performed at an oblique angle to the normal of the targeted point.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target. For instance, each contour path may be spaced away from a surface of the scan target based on a selected distance. The UAV may determine a plurality of image capture locations for each contour path. The image capture locations may indicate locations at which an image of a surface of the scan target is to be captured. The UAV may navigate along the plurality of contour paths based on a determined speed while capturing images of the surface of the scan target based on the image capture locations.

Abstract: In some examples, one or more processors of an aerial vehicle access a scan plan including a sequence of poses for the aerial vehicle to assume to capture, using the one or more image sensors, images of a scan target. A next pose of the scan plan is checked for obstructions, and based at least on detection of an obstruction, the one or more processors determine whether a backup pose is available for capturing an image of the targeted point orthogonally along a normal of the targeted point. Responsive to determining that the backup pose is unavailable for capturing an image of the targeted point orthogonally along the normal of the targeted point, image capture of the targeted point is performed at an oblique angle to the normal of the targeted point.

Abstract: In some examples, one or more processors of an unmanned aerial vehicle (UAV), control a propulsion mechanism of the UAV to cause the UAV to navigate to a plurality of positions in relation to a scan target. Using one or more image sensors of the UAV, a first image of the scan target is captured from a first position of the plurality of positions, and a second image of the scan target is captured from a second position of the plurality of positions. A disparity is determined between the first image captured at the first position and the second image captured at the second position. A three-dimensional model corresponding to the scan target is determined based in part on the disparity determined between the first image and the second image.

Abstract: In some examples, an image of a scan target is presented in a user interface on a display associated with a computing device. The user interface receives at least one user input indicating at least one point in a perimeter or edge of a volume for encompassing the scan target presented in the image of the scan target. A graphical representation of the volume in relation to the image of the scan target is generated in the user interface. Information for defining a location of at least a portion of the volume in three-dimensional space is sent to an unmanned aerial vehicle (UAV) to cause, at least in part, the UAV to scan at least a portion of the scan target corresponding to the volume.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may include one or more processors configured to capture, with one or more image sensors, and while the UAV is in flight, a plurality of images of a target. The one or more processors may compare a first image of the plurality of images with a second image of the plurality of images to determine a difference between a current frame of reference position for the UAV and an estimate of an actual frame of reference position for the UAV. In addition, the one or more processors may determine, based at least on the difference, and while the UAV is in flight, an update to a three-dimensional model of the target.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may identify a scan target. The UAV may navigate to two or more positions in relation to the scan target. The UAV may capture, using one or more image sensors of the UAV, two or more images of the scan target from different respective positions in relation to the scan target. For instance, the two or more respective positions may be selected by controlling a spacing between the two or more respective positions to enable determination of parallax disparity between a first image captured at a first position and a second image captured at a second position of the two or more positions. The UAV may determine a three-dimensional model corresponding to the scan target based in part on the determined parallax disparity of the two or more images including the first image and the second image.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may access a scan plan that includes a sequence of poses for the UAV to assume to capture images of a scan target using one or more image sensors. The UAV may check a next pose of the scan plan for obstructions. Responsive to detection of an obstruction, the UAV may determine a backup pose based at least on a field of view of the next pose. The UAV may control a propulsion mechanism to cause the UAV to fly to assume the backup pose. The UAV may capture, based on the backup pose and using the one or more image sensors, one or more images of the scan target.

Abstract: In some examples, an image of a scan target is presented in a user interface on a display associated with a computing device. The user interface receives at least one user input indicating at least one point in a perimeter or edge of a volume for encompassing the scan target presented in the image of the scan target. A graphical representation of the volume in relation to the image of the scan target is generated in the user interface. Information for defining a location of at least a portion of the volume in three-dimensional space is sent to an unmanned aerial vehicle (UAV) to cause, at least in part, the UAV to scan at least a portion of the scan target corresponding to the volume.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may include one or more processors configured to capture, with one or more image sensors, and while the UAV is in flight, a plurality of images of a target. The one or more processors may compare a first image of the plurality of images with a second image of the plurality of images to determine a difference between a current frame of reference position for the UAV and an estimate of an actual frame of reference position for the UAV. In addition, the one or more processors may determine, based at least on the difference, and while the UAV is in flight, an update to a three-dimensional model of the target.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may identify a scan target. The UAV may navigate to two or more positions in relation to the scan target. The UAV may capture, using one or more image sensors of the UAV, two or more images of the scan target from different respective positions in relation to the scan target. For instance, the two or more respective positions may be selected by controlling a spacing between the two or more respective positions to enable determination of parallax disparity between a first image captured at a first position and a second image captured at a second position of the two or more positions. The UAV may determine a three-dimensional model corresponding to the scan target based in part on the determined parallax disparity of the two or more images including the first image and the second image.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may access a scan plan that includes a sequence of poses for the UAV to assume to capture images of a scan target using one or more image sensors. The UAV may check a next pose of the scan plan for obstructions. Responsive to detection of an obstruction, the UAV may determine a backup pose based at least on a field of view of the next pose. The UAV may control a propulsion mechanism to cause the UAV to fly to assume the backup pose. The UAV may capture, based on the backup pose and using the one or more image sensors, one or more images of the scan target.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may determine, based on a three-dimensional (3D) model including a plurality of points corresponding to a scan target, a scan plan for scanning at least a portion of the scan target. For instance, the scan plan may include a plurality of poses for the UAV to assume to capture images of the scan target. The UAV may capture with one or more image sensors, one or more images of the scan target from one or more poses of the plurality of poses. Further, the UAV may determine an update to the 3D model based at least in part on the one or more images. Additionally, the UAV may update the scan plan based at least in part on the update to the 3D model.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target. For instance, each contour path may be spaced away from a surface of the scan target based on a selected distance. The UAV may determine a plurality of image capture locations for each contour path. The image capture locations may indicate locations at which an image of a surface of the scan target is to be captured. The UAV may navigate along the plurality of contour paths based on a determined speed while capturing images of the surface of the scan target based on the image capture locations.

Abstract: In some examples, an unmanned aerial vehicle (UAV) employs one or more image sensors to capture images of a scan target and may use distance information from the images for determining respective locations in three-dimensional (3D) space of a plurality of points of a 3D model representative of a surface of the scan target. The UAV may compare a first image with a second image to determine a difference between a current frame of reference position for the UAV and an estimate of an actual frame of reference position for the UAV. Further, based at least on the difference, the UAV may determine, while the UAV is in flight, an update to the 3D model including at least one of an updated location of at least one point in the 3D model, or a location of a new point in the 3D model.

Abstract: In some examples, an unmanned aerial vehicle (UAV) employs one or more image sensors to capture images of a scan target and may use distance information from the images for determining respective locations in three-dimensional (3D) space of a plurality of points of a 3D model representative of a surface of the scan target. The UAV may compare a first image with a second image to determine a difference between a current frame of reference position for the UAV and an estimate of an actual frame of reference position for the UAV. Further, based at least on the difference, the UAV may determine, while the UAV is in flight, an update to the 3D model including at least one of an updated location of at least one point in the 3D model, or a location of a new point in the 3D model.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may determine, based on a three-dimensional (3D) model including a plurality of points corresponding to a scan target, a scan plan for scanning at least a portion of the scan target. For instance, the scan plan may include a plurality of poses for the UAV to assume to capture images of the scan target. The UAV may capture with one or more image sensors, one or more images of the scan target from one or more poses of the plurality of poses. Further, the UAV may determine an update to the 3D model based at least in part on the one or more images. Additionally, the UAV may update the scan plan based at least in part on the update to the 3D model.

Abstract: A surgical retractor device for retaining and/or moving internal organs during minimally invasive or laparoscopic surgery is provided. The surgical retractor can be a single continuous structure that includes a shaft. The shaft can branch into a first elongate finger with a first distal end opposite the shaft and a second elongate finger with a second distal end opposite the shaft. The retractor can further include a resilient lattice structure disposed between the first elongate finger and the second elongate finger. The retractor can have an expanded configuration and a collapsed configuration based on relative distance between the first distal end and the second distal end. When the retractor is in the collapsed configuration, spring force energy can be stored in the resilient lattice structure.