Abstract: Apparatuses, systems, and techniques to grasp objects with a robot. In at least one embodiment, a neural network is trained to determine a grasp pose of an object within a cluttered scene using a point cloud generated by a depth camera.

Abstract: Various surgical systems are disclosed. A surgical system comprises a robotic tool, a robot control system, a surgical instrument, and a surgical hub. The robot control system comprises a control console and a control unit in signal communication with the control console and the robotic tool. The surgical hub comprises a display. The surgical hub is in signal communication with the robot control system. The surgical hub is configured to detect the surgical instrument and represent the surgical instrument on the display.

Abstract: A method of controlling a movement of a robot based on determination of a risk level includes: a risk level determining operation of determining a risk level related to a motion of the robot; and a robot control operation of controlling the movement of the robot based on the risk level, wherein the robot transfers an object. The determination of the risk level related to the motion of the robot includes: an internal risk level determining operation of determining an internal risk level based on an attribute of the object; and an external risk level determining operation of determining an external risk level related to an environmental state around the robot.

Abstract: An alignment apparatus includes a rotational support configured to rotate around a central axis, a rotation actuator, an edge sensor, and control circuitry. The rotational support includes substrate supports configured to concurrently support a substrate, and ring supports configured to concurrently support a focus ring. The rotation actuator is configured to rotate the rotational support around the central axis. The edge sensor is configured to generate an edge signal that changes in accordance with each of an edge position of the substrate and an edge position of the focus ring. The control circuitry is configured to control the rotation actuator to adjust a posture of the substrate to a first target posture based on the edge signal, and to control the rotation actuator to adjust a posture of the focus ring to a second target posture based on the edge signal.

Abstract: Systems and methods of servicing engines including a method of servicing an engine, the method including navigating at least a portion of a robotic assembly to a location associated with the engine; applying, from the robotic assembly, a medium to one or more adjustable components of the engine while the engine is at an elevated temperature; waiting a duration of time; and with the robotic assembly, operating on the one or more adjustable components.

Abstract: The invention relates to a method for controlling a robotic device (50) with modified control commands transmitted over a wireless network, wherein the robotic device (50) comprises a plurality of joints (53), wherein each joint represents one degree of freedom of the robotic device, the method comprising at a trajectory modification entity (100): —determining a load of the wireless network (30), —receiving a plurality of control commands controlling a planned trajectory of the robotic device (50) from a robotic control entity (70), each of the control commands configured to control one degree of freedom of a first number of degrees of freedom addressed by the plurality of control commands, —determining a reduced number of degrees of freedom for the modified control commands smaller than the first number based on the determined load, —determining the modified control commands based on the reduced number of degrees of freedom, wherein the modified control commands address a limited number of degrees of freedom

Abstract: Provided is a process, including: obtaining, with a computer system, a set of tasks to be performed by a fleet of robots; obtaining, with the computer system, for each task in the set of tasks, a respective plurality of duty cycles, each corresponding to an amount of usage of a respective actuator of a robot among the fleet of robots upon performing the respective task; accessing, with the computer system, for each robot in the fleet of robots, a current wear-state vector having dimensions corresponding to cumulative wear on actuators of the respective robots; and based on the current wear-state vectors and the duty cycles of the tasks, with the computer system, assigning the tasks to the robots in the fleet of robots.

Abstract: A system including an autonomous ground vehicle (“AGV”) designed as a common platform to which is affixed one or more articulated arms, which, when combined with attached implements and software for performing movement of the AGV and the arm(s), carries out tasks common to small farms and maintaining small parcels of land. The software enables a farm operator to set up, control, and monitor operations of the robotic system.

Abstract: The present invention relates to a computer-implemented method. The method includes causing a visual programming panel including a timeline editor and a plurality of motion blocks enabling a variety of robotic motions to be displayed in a visualization interface provided by a robot simulator shown on a web browser; selecting from a user, at the visual programming panel, at least one motion block from the plurality of motion blocks and adding the at least one motion block into the timeline editor, via a drag-and-drop, to form a motion configuration; and according to the motion configuration at the visual programming panel, automatically generating a program capable of commanding an end effector equipped on a target robot in a work cell to perform at least one selected robotic motion from the variety of robotic motions in the robot simulator.

Abstract: A method for adjusting the operation of a surgical instrument using machine learning in a surgical suite is disclosed.

Abstract: Various embodiments of the present technology generally relate to robotic devices, artificial intelligence, and computer vision. More specifically, some embodiments relate to an imaging process for detecting failure modes in a robotic motion environment. In one embodiment, a method of detecting failure modes in a robotic motion environment comprises collecting one or more images of a multiple scenes throughout a robotic motion cycle. Images may be collected by one or more cameras positioned at one or more locations for collecting images with various views. Images collected throughout the robotic motion cycle may be processed in real-time to determine if any failure modes are present in their respective scenes, report when failure modes are present, and may be used to direct a robotic device accordingly.

Abstract: Various embodiments of the technology described herein generally relate to systems and methods for trajectory optimization with machine learning techniques. More specifically, certain embodiments relate to using neural networks to quickly predict optimized robotic arm trajectories in a variety of scenarios. Systems and methods described herein use deep neural networks to quickly predict optimized robotic arm trajectories according to certain constraints. Optimization, in accordance with some embodiments of the present technology, may include optimizing trajectory geometry and dynamics while satisfying a number of constraints, including staying collision-free and minimizing the time it takes to complete the task.

Abstract: A vehicle speed control system that controls a vehicle speed of an agricultural vehicle that performs work using a work device while traveling using a traveling device, the agricultural vehicle performs work travel a plurality of times with non-work travel interposed therebetween, the vehicle speed control system including: a control unit configured to perform work travel control in which a vehicle speed is set according to a load on a motive power source that drives the traveling device and the work device; and a storage unit in which a vehicle speed that is set during the work travel is stored as an optimum vehicle speed, the control unit performs initial work travel control in which a vehicle speed at a time when the work travel is started after the non-work travel is set using the optimum vehicle speed that is stored during the work travel performed before the non-work travel.

Abstract: A method for temporal synchronization between an automatic movement device and a contactless detection device arranged on the automatic movement device in order to measure a physical parameter along at least one and the same defined trajectory along the surfaces of a plurality of materials to be evaluated.

Abstract: The present invention relates to a system for cleaning at least two sensors/transmitters for a motor vehicle, the system comprising at least one first device for projecting a cleaning fluid onto at least one first sensor/transmitter, at least one second device for projecting a cleaning fluid onto at least one second sensor/transmitter, at least one reservoir, at least one circuit for distribution of the cleaning fluid, connecting the reservoir to the first and second projection devices, at least one electronic pump, and at least one control unit, characterized in that the control unit is configured to receive information on a request for activation of the first and/or second projection device(s) in order to determine a theoretical value of at least one operating parameter of a pump.

Abstract: A method of controlling a movement of a robot based on determination of a risk level includes: a risk level determining operation of determining a risk level related to a motion of the robot; and a robot control operation of controlling the movement of the robot based on the risk level, wherein the robot transfers an object. The determination of the risk level related to the motion of the robot includes: an internal risk level determining operation of determining an internal risk level based on an attribute of the object; and an external risk level determining operation of determining an external risk level related to an environmental state around the robot.

Abstract: Embodiments of the present application relate to the technical field of robot control, and in particular, to an unmanned aerial vehicle (UAV) path planning method and apparatus and a UAV. The UAV path planning method includes: acquiring a depth map of an environment in front of a UAV; acquiring a grid map centered on a body of the UAV according to the depth map; determining candidate flight directions for the UAV according to the grid map; determining an optimal flight direction for the UAV from the candidate flight directions; and controlling the UAV to fly in the optimal flight direction to avoid an obstacle in the environment in front of the UAV. In this way, the embodiments of the present application can accurately determine an obstacle that suddenly appears in an unknown environment and a dynamic environment, so as to achieve real-time path planning.

Abstract: When an autonomous mobile robot is acquires enters a stuck state in which the autonomous mobile robot cannot autonomosly move, an autonomous mobile apparatus control system according to the present disclosure transmits an autonomous cancel notification for notifying the higher-level management apparatus that the autonomous mobile robot cannot autonomosly move, waits for an operation instruction from the higher-level management apparatus after the transmission of the autonomous cancel notification. The higher-level management apparatus gives an operation instruction to the autonomous mobile robot in response to receiving the autonomous cancel notification based on information acquired from at least one of the plurality of environment cameras. The autonomous mobile robot is configured to resume autonomous driving in response to safety confirmation based on a proximity sensor provided in the autonomous mobile robot after operating in accordance with the operation instruction.

Abstract: A robotic surgical system includes a robotic arm, a surgical device coupled with the robotic arm and configured to extend through a body wall of a patient, and a controller in communication with the robotic arm. The controller is configured to determine a position of the surgical device relative to the patient. The controller is also configured to acknowledge a maximum allowable metric associated with the body wall at the determined position, and determine a metric associated with the body wall at the determined position. The controller is furthermore configured to drive the robotic arm to manipulate the surgical device such that the determined metric does not exceed the maximum allowable metric.

Abstract: An apparatus, system and method of operating an autonomous mobile robot having a height of at least one meter. The robot body; at least two three-dimensional depth camera sensors affixed to the robot body proximate to the height, wherein the sensors are directed toward a floor surface and, in combination, comprise a substantially 360 degree field of view of the floor surface around the robot body; and a processing system for receiving pixel data within the field of view of the sensors; obtaining missing or erroneous pixels from the pixel data; comparing the missing or erroneous pixels to a template, wherein the template comprises at least an indication of ones of the missing or erroneous pixels indicative of the robot body and a shadow of the robot body; and outputting an indication of obstacles in or near the field of view based on the comparing.