An interactive living entity automatic sampling system includes a structure supporting components including a first sensor, a second sensor, a robotic arm, a camera, and a touchless interface, wherein the structure and the components are adapted for use in a clean room. The first sensor is adapted to sense the interactive living entity in response to the interactive living entity being at a predetermined position relative to the structure for a predetermined time. The second sensor is adapted to sense an indicia associated with the interactive living entity. In response to the second sensor sensing the indicia, the sampling system initiates an operating cycle, or continues the previously initiated operating cycle, for collecting a sample from the interactive living entity. During the operating cycle, the touchless interface provides positioning instructions to the interactive living entity in combination with the robotic arm handling a partially enclosed container for collecting the sample from the interactive living entity.

This patent proposal document provides a complete robot hand control scheme using myoelectric intention estimation of the human being using the kernel Principal Component Analysis Algorithm (kPCA). The robot hand system includes a biometric EMG sensor system, a robot hand including with multiple fingers, a controller connected with the biometric EMG sensor system, and a robot hand. The controller acquires the biometric EMG signal by means of a biometric sensor system, estimates myoelectric motion intention by applying the kernel principal component analysis (kPCA) algorithm using a kernel function, and delivers a control command corresponding to the estimated motion intention of the user to the robot hand.

Methods and systems to remotely operate robotic devices are provided. A number of embodiments allow users to remotely operate robotic devices using generalized consumer devices (e.g., cell phones). Additional embodiments provide for a platform to allow communication between consumer devices and the robotic devices. Further embodiments allow for training robotic devices to operate autonomously by training the robotic device with machine learning algorithms using data collected from scalable methods of controlling robotic devices.

A robot is provided. The robot includes a microphone, a camera, a communication interface including a circuit, a memory storing at least one instruction, and a processor, wherein the processor is configured to acquire a user voice through the microphone, identify a task corresponding to the user voice, determine whether the robot can perform the identified task, and control the communication interface to transmit information on the identified task to an external robot based on the determination result.

An electronic device may receive log information regarding a motion of a wearable device from the wearable device, determine a value of at least one of one or more mobile parameters to be applied to a robot parameter algorithm for calculating a value of a robot parameter used to control the wearable device based on the log information, and determine the value of the robot parameter based on the robot parameter algorithm and the determined value of at least one of the mobile parameters.

A computer is configured to receive a request from an autonomous machine to perform an action, authenticate the autonomous machine according to a smart contract blockchain program, generate encrypted commands to actuate one or more components of the autonomous machine to perform the action in response to authenticating the autonomous machine, transmit the encrypted commands to an external server configured to authenticate the request according to a blockchain program, receive decrypted commands from the external server based on authentication of the request, and actuate the one or more components of the autonomous machine to perform the action according to the decrypted commands.

A method for characterizing a state of an end effector of an ultrasonic device is disclosed. The ultrasonic device including an electromechanical ultrasonic system defined by a predetermined resonant frequency. The electromechanical ultrasonic system further including an ultrasonic transducer coupled to an ultrasonic blade. The method including applying, by an energy source, a power level to the ultrasonic transducer; measuring, by a control circuit coupled to a memory, an impedance value of the ultrasonic transducer; comparing, by the control circuit, the impedance value to a reference impedance value stored in the memory; classifying, by the control circuit, the impedance value based on the comparison; characterizing, by the control circuit, the state of the electromechanical ultrasonic system based on the classification of the impedance value; and adjusting, by the control circuit, the power level applied to the ultrasonic transducer based on the characterization of the state of the end effector.

Robots are commonly used for automated MIG (Metal Inert Gas) or TIG (Tungsten Inert Gas) welding in many industries such as automotive manufacturing. A weld procedure is defined and the robot performs motion control of the weld torch along the weld seam, while starting and stopping the arc as desired along the weld seams. The robot controls the motion of the torch along the weld path. The motion is defined by a combination of the position and orientation of the torch which is attached to the robot end-effector. The weld specification will generally prescribe a portion or all of the desired orientation of the torch. This information can be used to reduce the complexity of programming a weld path for a robot.

A robot teleoperation control device includes a first acquisition unit that acquires operator state information of a state of an operator who operates a robot, an intention estimation unit that estimates an intention of the operator to cause the robot to perform a motion on the basis of the operator state information, a second acquisition unit that acquires at least one of geometric information and dynamic information of the object, an operation method determination unit that determines a method of operating the object based on the estimated motion intention of the operator, and a control amount determination unit that determines a method of operating the robot and force during operation from the information acquired by the second acquisition unit and information determined by the operation method determination unit and reflects the result in a control instruction.

Various surgical systems are disclosed. A surgical system can include a surgical robot and a surgical hub. The surgical robot can include a control unit in signal communication with a control console and a robotic tool. The surgical hub can include a display. The surgical hub can be in signal communication with the control unit. A facility can include a plurality of surgical hubs that communicate data from the surgical robots to a primary server. To alleviate bandwidth competition among the surgical hubs, the surgical hubs can include prioritization protocols for collecting, storing, and/or communicating data to the primary server.