A method and robot controller configured to obtain an inertia-vibration model of the robot arm. The inertia-vibration model defines a relationship between the inertia of the robot arm and the vibrational properties of said robot arm and have been by setting the robot arm in a plurality of different physical configurations and for each of said physical configurations of said robot arm obtaining the vibrational properties and the inertia the robot arm. The inertia-vibration model makes it possible to in a simple and efficient way to obtain the vibrational properties of different physical configurations of the robot arm whereby the robot arm can be controlled according to the vibrational properties of the robot arm. This makes it possible to reduce the vibrations of the robot arm during movement of the robot arm.

System and techniques for tool position determination in a robotic appendage are described herein. A robotic appendage is put through a rotational movement to induce acceleration in a tool mounted to the appendage. A model for acceleration is created from positional kinematics of the appendage. A measurement of acceleration is taken at the tool and fit to the model to determine distance from the axis of rotation to the tool. The distance is provided for use in control or modeling of the robotic appendage.

The technology relates to a memory insertion machine for inserting memory modules into memory sockets on a circuit board. The memory insertion machine may include one or more insertion rods moveably mounted to one or more vertical guides and an insertion controller. The insertion controller may be configured to apply an insertion force to a memory module in a memory socket by controlling the movement of the one or more insertion rods on the one or more vertical guides. The movement of the one or more insertion rods may have a gradually decreasing deceleration as the insertion rods move towards the memory socket.

The present disclosure provides systems and methods for training a robot. The systems and methods may provide a robotic system. The robotic system may comprise a trainable robot and a sensor. The sensor may be attached to at least one physical tool. The method may comprise using the sensor to capture movement from a user operating the at least one physical tool. The method may include using at least the movement captured to train the robot, such that upon training, the robot may be trained to perform at least the movement.

A failure prediction method of predicting a failure of a component of a robot including a robot arm having the component and a detection section that detects information on vibration characteristics when the robot arm moves, includes generating a failure prediction model for prediction of the failure of the component by machine learning based on the information on vibration characteristics, and predicting the failure of the component based on an estimated value of failure prediction output by the generated failure prediction model when the information on vibration characteristics is input to the generated failure prediction model.

A robot system that performs desired processing on a processing target object using a processing tool. The robot system includes a robot having an arm tip that holds the processing tool, a position detector that detects a position of the arm tip, and a robot controller that controls an operation of the robot based on a position command and a position feedback detected by the position detector. The robot controller includes an adjustment operation creating unit that, during adjustment of operation parameters for controlling the operation of the robot, acquires an application and an operation area of the robot and automatically creates an adjustment operation corresponding to the acquired application and the operation area and a parameter adjustment unit that automatically adjusts the operation parameters during execution of the adjustment operation created by the adjustment operation creating unit so that a performance required for the application is satisfied.

A vibration analyzer includes a sensor that measures a vibration of an end effector supported by a distal end of a robot, a storage unit that stores a vibration calculation model of the robot, and a control unit configured to perform separation processing for separating a vibration to be reduced that is measured by the sensor into vibration data of the robot and vibration data of the end effector by using the vibration calculation model of the robot.

A robot system includes a robot mechanism unit provided with a sensor and a motor encoder for detecting a position of a control target, and a robot control device which controls an operation of the robot mechanism unit in accordance with an operation program, in which a learning control unit includes a position error estimating section which estimates low-frequency components in a position error, based on information from the motor encoder and estimates high-frequency components in the position error, based on information from the sensor.

A failure prediction method of predicting a failure of a component of a robot including a robot arm having the component and a detection section that detects information on vibration characteristics when the robot arm moves, includes generating a failure prediction model for prediction of the failure of the component by machine learning based on the information on vibration characteristics, and predicting the failure of the component based on an estimated value of failure prediction output by the generated failure prediction model when the information on vibration characteristics is input to the generated failure prediction model.

The technology relates to a memory insertion machine for inserting memory modules into memory sockets on a circuit board. The memory insertion machine may include one or more insertion rods moveably mounted to one or more vertical guides and an insertion controller. The insertion controller may be configured to apply an insertion force to a memory module in a memory socket by controlling the movement of the one or more insertion rods on the one or more vertical guides. The movement of the one or more insertion rods may have a gradually decreasing deceleration as the insertion rods move towards the memory socket.