A robotic repair unit (400) is presented that includes a removal tool (330, 425) coupled tot he robotic repair unit (400). The removal tool (330, 425) is configured to remove fluid or debris from a worksurface (130). The repair unit (400) also includes a controller (150) configured to control the robotic repair unit (400).

A friction compensation device of the present disclosure includes a drive torque calculation unit that calculates output torque of a transmission mechanism from a motor's position, velocity, and acceleration, the transmission mechanism being connected to a motor via a shaft to transmit the driving force of the motor, and a friction estimate value calculation unit that calculates a friction estimate value that is an estimate value of a friction force on the shaft. The friction estimate value calculation unit includes a friction correction value calculation unit that calculates a friction correction value to correct the friction force on the shaft, in accordance with the output of the drive torque calculation unit.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a demonstration device for robotic demonstration learning. One of the methods includes generating, by a demonstration device for a robot, a representation of a sequence of states input by a user of the demonstration device. The representation is provided by the demonstration device to a robot execution system. The representation of the sequence of actions is translated into a plurality of robot commands corresponding to the representation of the sequence of states input by the user on the demonstration device. The plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device are executed. Demonstration data is generated from one or more sensor streams of the robot while executing the plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device.

Systems and methods for detecting pose and force against an object are provided. A method includes receiving a signal from a deformable sensor comprising data from a deformation region in a deformable membrane resulting from contact with the object utilizing an internal sensor disposed within an enclosure and having a field of view directed through a medium and toward a bottom surface of the deformable membrane. The method also determines a pose of the object based on the deformation region of the deformable membrane. The method also determines an amount of force applied between the deformable membrane and the object is determined based on the deformation region of the deformable membrane.

Embodiments of the technology disclosed herein is directed to a medical manipulator capable of detecting an instant when a tip of the medical manipulator is unexpectedly separated from a body tissue and thus avoid making contact with surrounding body tissues. The technology disclosed eliminates the needs for providing a force sensor located on the tip of the medical manipulator. The medical manipulator includes a movable unit at one end and an electric motor, a control unit, and an operation input unit at opposed end thereof. The movable unit includes a treating unit for treating the body tissue. The electric motor is configured to operate the movable unit. The electric motor includes a current sensor or a torque detecting unit for detecting the torque of the motor. The control unit includes a torque reducing unit for reducing the torque transmitted to the movable unit from the electric motor.

An automated braiding machine for applying a braided cover to an elongate structure includes a barrel through which the elongate structure passes and a bobbin orbiting assembly configured to orbit a plurality of bobbins around the barrel. Each of the bobbins unwinds a corresponding thread having a portion extending between a rim of the barrel and the elongate structure. A first robotic arm assembly is configured to pull the elongate structure in a longitudinal direction thereof. A speed at which the elongate structure is pulled in the longitudinal direction thereof is dependent on a measured angle of one of the portions of the thread relative to a plane defined by the rim of the barrel.

A user control device for a surgical system. The surgical system includes a robotic manipulator to support and move a surgical instrument that has an energy applicator. One or more controllers operate the robotic manipulator in a semi-autonomous mode and calculate an instrument feed rate, which is the velocity at which the energy applicator advances along a tool path in the semi-autonomous mode. The user control device includes a housing configured as a pendant configured to be held in one hand of a user. A first control member is mounted to the housing and can be depressed to initiate operation of the robotic manipulator in the semi-autonomous mode. A second control member is mounted to the housing and can be depressed to modify the instrument feed rate in the semi-autonomous mode.

A method for training a neural network to derive, from an image of a camera mounted on a robot, a movement vector for the robot to insert an object into an insertion. The method includes controlling the robot to hold the object, bringing the robot into a target position in which the object is inserted in the insertion, for a plurality of positions different from the target position controlling the robot to move away from the target position to the position, taking a camera image by the camera and labelling the camera image by a movement vector to move back from the position to the target position and training the neural network using the labelled camera images.

A method for training a neural network to derive, from an image of a camera mounted on a robot, a movement vector to insert an object into an insertion. The method includes, for a plurality of positions in which the object held by the robot touches a plane in which the insertion is located controlling the robot to move to the position, taking a camera image by the camera and labelling the camera image with a movement vector between the position and the insertion in the plane and training the neural network using the labelled camera images.

A method of controlling a robot that performs work using an end effector on an object transported by a handler includes calculating a target position of the end effector based on a position of the object, calculating a tracking correction amount for correction of the target position in correspondence with a transport amount of the object, controlling the end effector to follow the object based on the target position and the tracking correction amount, acquiring an acting force acting on the end effector from the object using a force sensor, calculating a force control correction amount for correction of the target position to set the acting force to a target force, and controlling the acting force to be the predetermined target force by driving the manipulator based on the force control correction amount.