A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (AI) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures. In response to detection of the anatomical structures the AI system at least partially adjusts movement of the robotic surgical arms to avoid critical anatomical structures while performing the robotic surgery procedure to ensure precise targeting at the surgical site while minimizing damage to surrounding tissue at a surgical site. The AI system provides a surgeon with improved dexterity when the surgeon uses the robotic surgical arms at the surgical site, the improved dexterity resulting from at least partially analyzing the intraoperative data in real time by the one or more machine learning algorithms, enabling precise and adaptive manipulation of the robotic surgical arms at the surgical site.

Embodiments of the present disclosure may include an automated system for application of beehive treatment to a beehive, including a movable carriage, and a reservoir configured to hold the beehive treatment. Embodiments may also include a vision system disposed on the movable carriage and configured to detect an entrance of the beehive, an applicator system in fluid communication with the reservoir, the applicator system including an end effector configured to deliver the beehive treatment to the beehive through the entrance to the beehive. Embodiments may also include a controller in communication with the movable carriage, the vision system, and the applicator system.

A sewer inspection or maintenance system is provided having a sensor system with which at least three distances between a predetermined first point in the sewer pipe and the sewer wall of the sewer pipe are detected. The system has a processing unit adapted for determining a diameter of the sewer pipe and a predetermined second point in the sewer pipe based on the detected distances, and for determining a horizontal offset and a vertical offset between the predetermined first point and the predetermined second point based on the determined diameter and the detected distances. The system also has a positioning unit which is adapted to correct the position of an inspection unit in the sewer pipe by the two offsets. A corresponding method is provided as well.

This automated analysis support robot for carrying out an inspection of an analysis module that automatically analyzes a biological sample comprises a vehicle body, a camera mounted on the vehicle body, a communication device which communicates directly or indirectly with the analysis module, and a computer for controlling the vehicle body and the camera, wherein the computer: controls the vehicle body to move to a predetermined operating position and to face an inspection target provided in the analysis module; images the inspection target using the camera; and processes a video of the inspection target to calculate management data relating to the inspection target.

A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (AI) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures. In response to detection of the anatomical structures the AI system at least partially adjusts movement of the robotic surgical arms to avoid critical anatomical structures while performing the robotic surgery procedure to ensure precise targeting at the surgical site while minimizing damage to surrounding tissue at a surgical site. The AI system provides a surgeon with improved dexterity when the surgeon uses the robotic surgical arms at the surgical site, the improved dexterity resulting from at least partially analyzing the intraoperative data in real time by the one or more machine learning algorithms, enabling precise and adaptive manipulation of the robotic surgical arms at the surgical site.

An attachment for an unmanned aerial vehicle (UAV) for trimming tree branches. An articulating arm is mounted to the UAV with a battery powered chain saw positioned along the end of a second articulating arm. The chainsaw allows for the trimming of remote trees and bushes previously only accessible by a ladder or bucket lift. The payload is adjustable forward/aft to maintain the drones center of gravity. The drone includes a remote control receiver, and an antenna allowing an operator to control all aspects of the drone from a remote position.

A system and method for offboard monitoring are provided. The system may include a remote monitoring vehicle including one or more sensors, a drive mechanism for driving the remote monitoring vehicle; and a controller coupled to the one or more sensors and the drive mechanism. The controller may be configured to navigate the monitoring vehicle along a predetermined path of the industrial site; receive sensor data relating to an equipment; determine a state of the equipment based on the sensor data; determine whether the state of the equipment meets a threshold state for maintenance; and generate an alert indicating a maintenance event for the equipment when the state of the equipment meets the threshold state for maintenance.

A robot manipulator has a base with a connected arm by a shoulder joint, and a control system and force selector. Based on a target trajectory for a distal end of the arm instructions, a target motion and an effective force applied to the base that causes the base to execute the target motion is determined. An applied force on the robot manipulator results in a determination of a virtual ZMP force applied to the base that would either counteract an observed motion of a ZMP of the robot manipulator or act to move the ZMP back to within a predetermined support region, and/or an external force applied. Data defining the effective force and the virtual ZMP force and/or the external force applied to the base and determines a target force based on the data is received. The base executed a motion in response to the target force.

A mobile hydrogen fueling system that is configured to provide hydrogen fuel to a hydrogen storage tank of an aircraft includes a mobile hydrogen storage tank, a robotic arm connected to the mobile hydrogen storage tank having a nozzle configured to interconnect with a corresponding receptacle on the hydrogen storage tank of the aircraft and an autonomous vehicle configured to locate the mobile hydrogen storage tank in a position near the aircraft to allow the robotic arm to interconnect the nozzle to the corresponding receptacle. A method of providing hydrogen fueling to a hydrogen storage tank of an aircraft is also presented.

Motion control integration including: a centralized integration system including data storage, a user interface, and multiple network connections; a first motion platform connected to the centralized integration system; a second motion platform connected to the centralized integration system; and a shared clock, where the centralized integration system shares clock data with the first motion platform and the second motion platform.