A system for controlling an operation of a machine including a plurality of actuators assisting one or multiple tools to perform one or multiple tasks, in response to receiving an acoustic mixture of signals generated by the tool performing a task and by the plurality of actuators actuating the tool, submit the acoustic mixture of signals into a neural network trained to separate from the acoustic mixture a signal generated by the tool performing the task from signals generated by the actuators actuating the tool to extract the signal generated by the tool performing the task from the acoustic mixture of signals, analyze the extracted signal to produce a state of performance of the task, and execute a control action selected according to the state of performance of the task.

The arithmetic device configured to perform a calculation for controlling a motion of a grasping apparatus that performs work involving a motion of sliding a grasped object includes: an acquisition unit configured to acquire a state variable indicating a state of the grasping apparatus during the work; a storage unit storing a learned neural network that has been learned by receiving a plurality of training data sets composed of a combination of the state variable acquired in advance and correct answer data corresponding to the state variable; an arithmetic unit configured to calculate a target value of each of various actuators related to the work of the grasping apparatus by inputting the state variable to the learned neural network read from the storage unit; and an output unit configured to output the target value of each of the various actuators to the grasping apparatus.

A robotic dock for video conferencing is described. In some embodiments, a dock may be configured to receive an Information Handling System (IHS), the dock comprising: a motor; a microcontroller coupled to the motor; and a memory coupled to the microcontroller, the memory having program instructions stored thereon that, upon execution by the microcontroller, cause the dock to control the motor to rotate the IHS toward or away from a participant of a video conference.

An equipment failure diagnosis apparatus, an equipment failure diagnosis method, a smart factory system, and an application agent configured to generate a virtual abnormal signal based on a normal signal data stored in the database, determine whether an equipment signal is an abnormal signal based on a virtual abnormal signal data for the virtual abnormal signal, and output a determination result information. Accordingly, the present disclosure can quickly and accurately diagnose a failure of equipment in a factory, even under conditions where labeling data is not present or insufficient.

Optimising water use in a way that avoids over watering or at least avoids or minimises water mobilisation may be useful. An irrigation control system is described, the system including a sound emitter arranged to emit sound towards a ground surface; a sound receiver arranged to receive sound emitted by the sound emitter and reflected or scattered from the ground surface. A controller then controls one or more irrigation parameters of an irrigator based at least in part on sound received by the sound receiver. In a further aspect, the irrigation control system senses the onset of surface water pooling or free water flow on the ground surface and the controller then controls irrigation parameters to reduce application of water in response to the sensed features. Related methods of controlling irrigation systems are also described.

A monitoring and inspection system for a work area includes a non-visual sensory detection sensor, such as a microphone or vibration detection sensor, and a processor. The sensor is configured to sense sounds or vibrations generated in the work area during the performance of an action that are then received by the processor. The processor analyzes the received acoustic and/or vibrational signals and compares the received signals to an expected signal to verify that the identified acoustic and/or vibration signature of the detected signal is an acoustic and/or vibration signature associated with the operational step that was performed to confirm that the operational step has been performed, and that it has been performed properly.

A system for controlling an operation of a machine including a plurality of actuators assisting one or multiple tools to perform one or multiple tasks, in response to receiving an acoustic mixture of signals generated by the tool performing a task and by the plurality of actuators actuating the tool, submit the acoustic mixture of signals into a neural network trained to separate from the acoustic mixture a signal generated by the tool performing the task from signals generated by the actuators actuating the tool to extract the signal generated by the tool performing the task from the acoustic mixture of signals, analyze the extracted signal to produce a state of performance of the task, and execute a control action selected according to the state of performance of the task.

[Problem] To provide an abnormal-sound detection device in which incorrect detection is rare. [Solution] An abnormal-sound detection device has an imaging means, an operation range identification means, a sound collection means, an abnormal-sound detection means, an abnormal-sound generation position identification means, and an abnormal-sound source determination means. The imaging means captures an image of a diagnosis object. The operation range identification means identifies and stores the operation range of the diagnosis object on the basis of the image captured by the imaging means. The sound collection means collects sounds arriving from the diagnosis object and the vicinity thereof. The abnormal-sound detection means detects abnormalities in sounds included in the collected sounds. When an abnormality in a sound is detected by the abnormal-sound detection means, the abnormal-sound generation position identification means identifies the position at which the abnormality of the sound was generated. The abnormal-sound source determination means compares the operation range and the abnormal-sound generation position of the diagnosis object, and determines whether the abnormality of the sound is derived from an abnormality of the diagnosis object.

A robotic dock for video conferencing is described. In some embodiments, a dock may be configured to receive an Information Handling System (IHS), the dock comprising: a motor; a microcontroller coupled to the motor; and a memory coupled to the microcontroller, the memory having program instructions stored thereon that, upon execution by the microcontroller, cause the dock to control the motor to rotate the IHS toward or away from a participant of a video conference.

A robotic dock for video conferencing is described. In some embodiments, a dock may be configured to receive an Information Handling System (IHS), the dock comprising: a motor; a microcontroller coupled to the motor; and a memory coupled to the microcontroller, the memory having program instructions stored thereon that, upon execution by the microcontroller, cause the dock to control the motor to rotate the IHS toward or away from a participant of a video conference.