An adjustment support device includes: a storage unit for storing, with force state data and position data in an operation when performing force control of the industrial robot as a state variable and with data indicating a result of determining whether a result of the force control is success or failure based on predetermined criteria as determination data, a learning model generated by machine learning; an analysis unit for analyzing the learning model to analyze, for a control parameter used when the force control of the industrial robot has failed, an adjustment method of the control parameter for improving a degree of success of the force control; and an adjustment determination unit for determining, based on a result of the analysis by the analysis unit, an adjustment method of the control parameter in the force control used when the force control has failed and outputting the adjustment method.

A method of presenting a takt time includes a first step of acquiring first information on a type of a first object or a second object and second information on a movement direction of the first object during the work, a second step of acquiring third information on a takt time taken for the work by using a table prepared with respect to each combination of the first information and the second information and showing relationships between a force control parameter and a takt time corresponding to the force control parameter, and associating the first information and the second information acquired at the first step with the table, and a third step of presenting the third information acquired at the second step.

A first step of executing a first operation to bring a hand placed on a robot arm or a first object held by the hand into contact with a second object based on a first force control parameter, a second step of acquiring information of an external force applied to the robot arm by executing a second operation different from the first operation on a robot with the hand or the first object in contact with the second object, a third step of acquiring information of external rigidity based on the acquired external force information, and a fourth step of changing the force control parameter from the first force control parameter to a second force control parameter acquired based on the acquired external rigidity information and a position of a control point corresponding to the acquired external rigidity information are provided.

A robot control device includes a modification work trained model building section. The modification work trained model building section builds a modification work trained model by training on modification work data when a user's modification operation is performed to intervene in a provisional operation of a robot arm to perform a series of operations. In the modification work data, input data is a state of the robot arm and its surroundings when the robot arm is operating and output data is data of the operation by a user for modifying the provisional operation or the modification operation of the robot arm by the user's operation for modifying the provisional operation.

A component installation system includes an engagement clamp having a circular shape coupled to a robotic arm, being configured to engage an annular component. The component installation system further includes an actuator coupled to the engagement clamp and operable to cause the engagement clamp to engage and disengage the annular component, and a heating element coupled to the engagement clamp and arranged to heat the annular component engaged within the engagement clamp. The component installation system further includes a controller in communication with the robotic arm, the actuator and the heating element.

A metallurgical technology probe insertion calibration method employing visual measurement and an insertion system thereof are provided. A vision sensor (5), a cylindrical rod (1), and a metallurgical technology probe (2) are used to construct an agreed region (6). In the agreed region (6), the vision sensor (5) acquires relative positions and orientations of the cylindrical rod (1) and the metallurgical technology probe (2), and an acquired position and orientation result is used to control a driving device (3) to insert the cylindrical rod (1) into the metallurgical technology probe (2). To improve the accuracy and reliability of the insertion, a standard probe (7) and a fixing device (4) are used together to perform effective calibration on an initial position, orientation, and axis in the insertion.

Disclosed are various embodiments of a three-dimensional perception and object manipulation robot gripper configured for connection to and operation in conjunction with a robot arm. In some embodiments, the gripper comprises a palm, a plurality of motors or actuators operably connected to the palm, a mechanical manipulation system operably connected to the palm, a plurality of fingers operably connected to the motors or actuators and configured to manipulate one or more objects located within a workspace or target volume that can be accessed by the fingers. A depth camera system is also operably connected to the palm. One or more computing devices are operably connected to the depth camera and are configured and programmed to process images provided by the depth camera system to determine the location and orientation of the one or more objects within a workspace, and in accordance therewith, provide as outputs therefrom control signals or instructions configured to be employed by the motors or actuators to control movement and operation of the plurality of fingers so as to permit the fingers to manipulate the one or more objects located within the workspace or target volume. The gripper can also be configured to vary controllably at least one of a force, a torque, a stiffness, and a compliance applied by one or more of the plurality of fingers to the one or more objects.

A control device adapted to control a robot including a robot arm provided with a force detector includes a processor that is configured to execute computer-executable instructions so as to control the robot, wherein the processor is configured to: operate the robot arm to move a screw gauge which is disposed on a tip side of the force detector of the robot arm, used for an inspection of a screw hole, and provided with an external thread, to make the external thread have contact with the screw hole; then detect force applied to the screw gauge using the force detector to perform force control in a direction perpendicular to a direction of an axis of the screw hole based on detection information of the force detector; and operate the robot arm to move the screw gauge based on the force control.

A control device comprising a processor that is configured to execute computer-executable instructions so as to control a robot, wherein the processor is configured to: control a robot with force control on the basis of a force detected by a force detecting device, determine pass/fail of a result of fitting work in which the robot holds an object and fits the object in an object to be fit, control the robot with the force control in the fitting work, and determine the pass/fail on the basis of whether a portion where the force detected by the force detecting device decreases by a first value or more is present in the fitting work.

A robot system includes a robot, state detection sensors to, a timekeeping unit, a learning control unit, a determination unit, an operation device, and an input unit, and an additional learning unit. The determination unit determines whether or not the work of the robot can be continued under the control of the learning control unit based on the state values detected by the state detection sensors to and outputs determination result. The additional learning unit performs additional learning of the determination result indicating that the work of the robot cannot be continued, the operator operation force, work state output by the operation device and the input unit, and timer signal output by the timekeeping unit.