Techniques for inter-arm registration include a computer-assisted system having a repositionable arm and a control unit coupled to the repositionable arm. The control unit is configured to receive, from an imaging device, image data of an instrument, the instrument mounted to the repositionable arm; determine an observed geometric property of a feature set of the instrument based on the image data, the feature set comprising at least one feature; determine an expected geometric property of the feature set based on at least kinematic data of the repositionable arm; determine a difference between the observed geometric property and the expected geometric property; update, based on the difference. a registration transform to produce an updated registration transform associated with the instrument; and control the instrument using the updated registration transform.

Systems, devices, and methods for time calibration. The method can include, in responses to receiving sensing data which indicates a deviation of a tool from an object to be operated by a robot with the tool, triggering the robot to perform a plurality of transformations. Each transformation causing the tool to contact the object at a reference position; determining joint positions of a joint of the robot holding the tool or the object after the plurality of transformations; and determining a position relationship between the tool and the robot at least partially based on the joint positions and the reference position.

A process for marking the real position and real orientation of a tool in relation to the manipulator arm of a robot. The process utilizes the amplitude measurements of acoustic signals and the flight time measurement of the acoustic waves emitted by an acoustic probe of the tool and reflected by the fixed reference elements. The position of the center of reference of the probe relative to the end of the manipulator arm is determined. The axes X and Y defining the plane of the probe along reference axes X and Y of known orientations are oriented so that the modification of the position and of the orientation of the probe in the reference frame can be defined. The displacements of the manipulator arm are managed by the controller based on the position of the probe in relation to the manipulator arm and the reference orientation of the probe.

Systems and methods are disclosed that determine a mapping between a first camera system's coordinate system and a second camera system's coordinate system; or determine a transformation between a robot's coordinate system and a camera system's coordinate system, and/or locate, in a robot's coordinate system, a tool extending from an arm of the robot based on the tool location in the camera's coordinate system. The disclosed systems and methods may use transformations derived from coordinates of features found in one or more images. The transformations may be used to interrelate various coordinate systems, facilitating calibration of camera systems, including in robotic systems, such as an image-guided robotic systems for hair harvesting and/or implantation.

Provided is a method for improved hand-eye calibration method based on a structured light camera. The method includes: step 1: establishing a pinhole camera model, and using a depth camera to detect a three-dimensional (3D) coordinate to obtain a physical coordinate of each point in an image coordinate system with a known depth relative to a camera coordinate system; step 2: establishing a Denavit-Hartenberg (DH) model of a robotic arm, and moving the robotic arm to a determined coordinate using inverse kinematics; step 3: collecting n sets of point cloud data, applying depth scaling coefficients to the n sets of point cloud data to perform Singular Value Decomposition (SVD), and solving for an optimal depth scaling coefficient using a Nelder-Mead algorithm; and step 4: completing the hand-eye calibration of the robotic arm based on the solved optimal depth scaling coefficient. The method offers strong operability and robustness.