A robot system includes a manipulator having a plurality of axes and driven by a motor provided for each axis, a robot controller, an encoder attached to the motor for each axis, an encoder wiring line connecting the encoder with the robot controller, a storage part in the manipulator which stores mechanical parameters including identification information for discriminating the encoder for each axis, and a control part in the robot controller which reads out the mechanical parameters from the storage part and communicates with the encoder through the encoder wiring line. The control part discriminates whether the identification information read out from the encoder and the identification information included in the mechanical parameters are coincided with each other or not for each axis and, when both the identification informations are not coincided with each other, the control part determines that erroneous wiring exists in the encoder wiring line.

As a preferred embodiment of the present invention, a device for controlling a collaborative robot includes a collision detection unit configured to sense a collision of the collaborative robot; a control unit configured to control an operation mode of the collaborative robot when the collision detection unit senses the collision; and a collision countermeasure unit configured to apply, when the collision detection unit senses the collision, a collision compensation value to each of a plurality of joints in the collaborative robot so as to change a proceeding direction of a force applied to the each of the plurality of joints.

A suction apparatus includes a suction unit, a negative pressure detection unit, a suction abnormality determination unit, and a notification unit. The suction unit suctions and holds merchandise with a negative pressure. The negative pressure detection unit detects a negative pressure value in the suction unit whenever the suction unit suctions the merchandise. The suction abnormality determination unit determines that the suction unit is abnormal in a case where the detected negative pressure value is lower in negative pressure degree than a predetermined suction determination negative pressure value continuously by a predetermined number of times of determination or more. The notification unit provides a notification in a case where the suction unit is determined to be abnormal.

A package imaging system can be configured to utilize unused or idle degrees of freedom associated with a robot to collect identification and modeling information. One or more sensors can be attached to the robot and configured to track a package between a first location and a second location. A final joint of the robot can be configured to cause one or more rotations of the package within the reference frame. The one or more sensors can capture one or more images of the package within the reference frame. Based on the one or more images, the package imaging system can determine a package identity from an identifier associated with the package. The package imaging system can also generate a three-dimensional model of the package by combining the one or more pictures.

A technique for analyzing Quality of Experience, QoE, of a delay critical robotic application in a cloud robotics system is disclosed, the robotic application involving use of a cloud based service by a robot, the service being provided to the robot from a cloud using a connection over a mobile communication network. A method implementation of the technique comprises triggering (S202) determining whether a QoE measure associated with the robotic application exceeds a threshold to assess whether QoE degradation is present, and, when it is determined that QoE degradation is present, triggering (S204) identifying a root cause for the QoE degradation based on one or more performance indicators observed within the mobile communication network and associated with the connection.

A method for controlling and/or monitoring a machine arrangement having at least one machine, in particular at least one robot, with the aid of a processor arrangement having a plurality of processors each with at least one core. The method includes selecting, in particular temporarily selecting, a first available and at least one further available core on the proviso that these cores are implemented, in particular arranged, on different processors of the processor arrangement, in particular during operation of the machine arrangement and/or on the basis of an updated directory and/or on the basis, in particular as a result, of an ascertained need for redundant processing of process signals; processing process signals redundantly with the aid of these selected cores; and controlling and/or monitoring the machine arrangement on the basis of this processing.

The progress of deterioration of a manufacturing facility is prevented while keeping KPI within an allowable range. A facility diagnosis device includes a deterioration prevention mode definition storage unit that stores information including an operation control method for preventing deterioration of a manufacturing facility or a portion thereof for each of predetermined deterioration prevention modes; a KPI calculation unit that calculates a predetermined KPI by using a deterioration degree predicted for each of the deterioration prevention modes for the manufacturing facility or the portion of the manufacturing facility, and determines whether the KPI satisfies a predetermined condition; a deterioration prevention determination unit that determines a deterioration prevention mode that should be executed from a satisfaction determination result; and a control information output unit that outputs control information on the manufacturing facility or the portion of the manufacturing facility according to the deterioration prevention mode that should be executed.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating safety trajectories. One of the methods comprises causing, by a robotic control system, execution of a robotic control plan by a plurality of robotic components in a robotic execution environment; generating a safety trajectory at each of a plurality of time points during the execution of the robotic control plan, including: obtaining data identifying a current position of a particular robotic component of the plurality of robotic components; generating, using the obtained data, a safety trajectory for the particular robotic component; and providing the safety trajectory to an emergency control system; determining that an emergency condition has been met; and in response, transferring control of the particular robotic component from the robotic control system to the emergency control system, comprising causing, by the emergency control system, execution of the safety trajectory by the particular robotic component.

A failure prediction device is provided with a machine learning device configured to learn the state of a brake of a motor with respect to data on the brake. The machine learning device observes brake operating state data indicative of an operating state of the brake when the brake is in a normal state, as state variables representative of a current environmental state, and uses the observed state variables to learn a distribution of the state variables with the brake in the normal state.

Systems and methods for detecting an escalator in a surrounding environment by a robotic apparatus are disclosed herein. According to at least one exemplary embodiment, an escalator may be determined based on an escalator detection parameter being met. The escalator detection parameter my further require detection of two side walls separated by a distance equal to a width of an escalator and detection of a depreciation in a floor equal to that observed between a stationary portion and a moving first step of an escalator.