A control device includes a processor that is configured to execute computer-executable instructions so as to control a robot, wherein the processor is configured to calculate a force control parameter related to force control of a robot by using machine learning, and control the robot on the basis of the calculated force control parameter.

Provided are a controller and a machine learning device that perform machine learning to optimize the servo gain of a machine inside a facility in accordance with action conditions, action environments, and a priority factor of the machine. Disclosed is a control system including: a state observation section that observes machine information on a machine as state data; a determination data acquisition section that acquires information on machining by a machine as determination data; a reward calculation section that calculates a reward based on the determination data and reward conditions; a learning section that performs the machine learning of the adjustment of the servo gain of the machine; a decision making section that determines an action of adjustment of the servo gain of the machine, based on the state data and a machine learning result of the adjustment of the servo gain of the machine; and a gain changing section that changes the servo gain of the machine, based on the action of adjustment of the determined servo gain.

A method of temperature control is applied to a cabinet in which a fan is disposed and the fan runs based on an input signal. The method includes obtaining a temperature signal corresponding to the cabinet, calculating a deviation signal between the input signal and the temperature signal, executing fuzzy learning to obtain a first proportional parameter, a first integral parameter and a first derivative parameter based on the deviation signal, generating a driver signal to execute a proportional-integral-derivative (PID) control based on the first proportional parameter, the first integral parameter and the first derivative parameter, wherein the driver signal is for driving the fan to adjust a temperature of the cabinet.

Methods, apparatuses, and systems associated with anomaly detection and resolution are described. Examples can include detecting, via a sensor of a robot, an object in a path of the robot while the robot is performing a task in an environment and classifying the object as an anomaly or a non-anomaly and the environment as anomalous or non-anomalous using a machine learning model. Examples can include proceeding with the task responsive to classification of the object as a non-anomaly and the environment as non-anomalous and resolving the anomaly or the anomalous environment and proceeding with the task responsive to classification of the object as an anomaly or the environment as anomalous.

Methods, apparatuses, and systems associated with anomaly detection and resolution are described. Examples can include detecting, via a sensor of a robot, an object in a path of the robot while the robot is performing a task in an environment and classifying the object as an anomaly or a non-anomaly and the environment as anomalous or non-anomalous using a machine learning model. Examples can include proceeding with the task responsive to classification of the object as a non-anomaly and the environment as non-anomalous and resolving the anomaly or the anomalous environment and proceeding with the task responsive to classification of the object as an anomaly or the environment as anomalous.