Certain aspects relate to systems with robotically controllable field generators and applications thereof. In one application, a robotic medical system, comprising a first robotic arm coupled to an electromagnetic (EM) field generator configured to generate an EM field, an EM sensor, and a processor. The processor may be configured to transmit a command to the first robotic arm to cause movement of the EM field generator along a robotic trajectory while the EM sensor remains at a location. An EM sensor trajectory of the EM sensor within the EM field corresponding to a period of time in which the EM field generator moved along the robotic trajectory may be detected. The robotic trajectory and the EM sensor trajectory may be analyzed to determine a difference between the robotic trajectory and the EM sensor trajectory; and EM distortion at the location may be detected comparing the difference and a threshold.

Techniques relate to determining a region associated with an object to assist in controlling a robotic arm. For example, a system can determine that the robotic arm is positioned adjacent to an object within an environment. The system can determine a region in the environment that is associated with the object based at least in part on a position of a distal end of the robotic arm. The system can control the robotic arm or another robotic arm to move in the environment based at least in part on the region.

A surgical method is provided for use with a teleoperated surgical system (surgical system), the method comprising: recording surgical instrument kinematic information indicative of surgical instrument motion produced within the surgical system during the occurrence of the surgical procedure; determining respective kinematic signatures associated with respective surgical instrument motions; producing an information structure in a computer readable storage device that associates respective kinematic signatures with respective control signals; comparing, during a performance of the surgical procedure surgical instrument kinematic information during the performance with at least one respective kinematic signature; launching, during a performance of the surgical procedure an associated respective control signal in response to a match between surgical instrument kinematics during the performance and a respective kinematic signature.

A surgical system includes a motor, a first link movable by operation of the motor, a plurality of non-driven, revolute joints coupled to the first link such that the first link separates the plurality of revolute joints from the motor, and an end effector coupled to the first link via the plurality of non-driven, revolute joints.

A method of operating a robotic control system comprising a master apparatus in communication with an input device having a handle and a slave system having a tool having an end effector whose position and orientation is determined in response to a position and orientation of the handle. The method involves producing a desired end effector position and a desired end effector orientation of the end effector, in response to a current position and a current orientation of the handle. The method further involves causing the input device to provide haptic feedback that impedes translational movement of the handle, while permitting rotational movement of the handle and preventing movement of the end effector, when a rotational alignment difference between the handle and the end effector meets a first criterion. The method further involves re-enabling translational movement of the handle when the rotational alignment difference meets a second criterion.

A method for a robotic surgical system includes displaying a graphical user interface on a display to a user, wherein the graphical user interface includes a plurality of reconfigurable display panels, receiving a user input at one or more user input devices, wherein the user input indicates a selection of at least one software application relating to the robotic surgical system, and rendering content from the at least one selected software application among the plurality of reconfigurable display panels.

A surgical system includes a motor, a first link movable by operation of the motor, a plurality of non-driven, revolute joints coupled to the first link such that the first link separates the plurality of revolute joints from the motor, and an end effector coupled to the first link via the plurality of non-driven, revolute joints.

An apparatus for providing haptic guidance during manipulation of an end-effector includes a robotic arm. The robotic arm has at least one actuated joint, at least one other joint connected to the at least one actuated joint, and a physical constraint movable by actuation of the at least one actuated joint. The physical constraint limits the motion of the at least one other joint in at least one direction. The apparatus further includes an end-effector configured to be manipulated by an application of external forces and connected to the at least one other joint.

A method for limiting joint velocity of a plurality of joints of a surgical robotic system, the surgical robotic system comprising a robot having a base and an arm extending from the base to an attachment for an instrument, the arm comprising a plurality of joints whereby the configuration of the arm can be altered, the method comprising: obtaining joint states for a first group of k joints of the arm, where k>1; for each of the k joints: determining from the obtained joint state a permitted range of motion for that joint; deriving, using the permitted range of motion, a joint velocity limit for that joint; selecting the minimum joint velocity limit of the k joints to be a common joint velocity limit used to limit each of the k joints individually; and calculating drive signals for driving the k joints wherein the velocity of each of the k joints is limited using the common joint velocity limit.

A generative adversarial network (GAN) (21, 24), or any other generative modeling technique, is used to learn (12) how to generate (68) an optimal robotic system given performance, operation, safety, or any other specifications. For instance, the specifications may be modeled (65) relative to anatomy to confirm satisfaction of anatomy-based or another task specific constraint. A machine-learning system, for instance neural network, is trained (12) to translate given specifications to a robotic configuration. The network may convert task-specific specifications into one or more configurations of robot modules into a robotic system. The user may enter (67) changes to performance in order for the network to estimate (62) appropriate configurations. The configurations may be converted (64) to estimated performance by another machine-learning system, for instance neural network, allowing modeling (65) of operation relative to the anatomy, such as anatomy based on medical imaging. The configuration satisfying the constraints from the modeling (65) may be assembled (69) and used.