Abstract: A robot system 100 includes a robot 1 that processes a processing portion B of an object W, a storage 32 that holds an image of the object W and three-dimensional information on the object W, a selector 9 that selects the processing portion B from the image, and a controller 3 that controls the robot 1. The controller 3 derives the processing portion B in the three-dimensional information based on a portion selected in the image by the selector 9 and the three-dimensional information, and moves the robot 1 based on the three-dimensional information on the processing portion B to cause the robot 1 to process the processing portion B.

Abstract: A robot control device includes: a trained model built by being trained on work data; a control data acquisition section which acquires control data of the robot based on data from the trained model; base trained models built for each of a plurality of simple operations by being trained on work data; an operation label storage section which stores operation labels corresponding to the base trained models; a base trained model combination information acquisition section which acquires combination information when the trained model is represented by a combination of a plurality of the base trained models, by acquiring a similarity between the trained model and the respective base trained models; and an information output section which outputs the operation label corresponding to each of the base trained models which represent the trained model.

Abstract: A specific point detection system includes an imager that acquires an image of an object W, a first detector that detects, using a first detection model learned by machine learning, a burr B included in the object W by taking the image acquired by the imager as input, a three-dimensional scanner that acquires three-dimensional information on the object W including the burr B detected by the first detector, and a second detector that re-detects, using a second detection model learned by machine learning, the burr B by taking the three-dimensional information acquired by the three-dimensional scanner as input.

Abstract: A robot system (1) includes the robot (10), a motion sensor (11), a surrounding environment sensor (12, 13), an operation apparatus (21), a learning control section (41), and a relay apparatus (30). The robot (10) performs work based on an operation command. The operation apparatus (21) detects and outputs an operator-operating force applied by the operator. The learning control section (41) outputs a calculation operating force. The relay apparatus (30) outputs the operation command based on the operator-operating force and the calculation operating force. The learning control section (41) estimates and outputs the calculation operating force by using a model constructed by performing the machine learning of the operator-operating force, the surrounding environment data, the operation data, and the operation command based on the operation data and the surrounding environment data outputted by the sensors (11 to 13), and the operation command outputted by the relay apparatus (30).

Abstract: 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.

Abstract: The robot teaching method includes a pre-registration step, robot operation step, and teaching step. The pre-registration step is for specifying a relative self-position of a measuring device with respect to surrounding environment by measuring the surrounding environment using the measuring device, and registering an environment teaching point that is a teaching point of the robot specified using the relative self-position. The robot operation step for automatically operating the robot so that the relative self-position of the robot with respect to the surrounding environment become equal to the environment teaching point in a state where the measuring device is attached to the robot. The teaching step for registering a detection value of a position and a posture of the robot measured by an internal sensor as teaching information in a state where the relative self-position of the robot with respect to the surrounding environment become equal to the environment teaching point.

Abstract: A training data screening device includes a data evaluation model, a data evaluator, a memory, and a training data screener. The data evaluation model is constructed by machine learning on at least a part of the collected data, or by machine learning on data different from the collected data. The data evaluator evaluates the input collected data using the data evaluation model. The memory stores the evaluated data, which is the collected data evaluated by the data evaluator. The training data screener screens the training data tier constructing the learning model from the evaluated data stored by the memory by an instruction of an operator to whom an evaluation result of the data evaluator is presented, or automatically screens the training data based on the evaluation result.

Abstract: A robot control device includes: a trained model built by being trained on work data; a control data acquisition section which acquires control data of the robot based on data from the trained model; base trained models built for each of a plurality of simple operations by being trained on work data; an operation label storage section which stores operation labels corresponding to the base trained models; a base trained model combination information acquisition section which acquires combination information when the trained model is represented by a combination of a plurality of the base trained models, by acquiring a similarity between the trained model and the respective base trained models; and an information output section which outputs the operation label corresponding to each of the base trained models which represent the trained model.

Abstract: 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.

Abstract: A robot control device includes: a learned model created through learning work data composed of input and output data, the input data including states of a robot and the surroundings where humans operate the robot to perform a series of works, the output data including human operation corresponding to the case or movement of the robot caused thereby; a control data acquisition section that acquires control data by obtaining output data related to human operation or movement from the model, being presumed in response to and in accordance with the input data; a completion rate acquisition section acquiring a completion rate indicating to which progress level in the series of works the output data corresponds; and a certainty factor acquisition section that acquires a certainty factor indicating a probability of the presumption in a case where the model outputs the output data in response to the input data.

Abstract: The information projection system includes stereo cameras, a controller, and projectors. The controller has a communication device, an analysis unit, a registration unit, and a projection control unit. The communication device acquires sets of appearance information in which each stereo camera detects an appearance of a workplace. The analysis unit analyzes the sets of appearance information, and creates a map information indicating shapes and positions of objects existing in the workplace. The registration unit creates and registers a work status information based on the map information that is individually created from the sets of appearance information respectively detected by the plurality of stereo cameras. The projection control unit creates an auxiliary image for assisting a work based on the work status information, and outputs the auxiliary image to each projector.

Abstract: A robot system (1) includes the robot (10), a motion sensor (11), a surrounding environment sensor (12, 13), an operation apparatus (21), a learning control section (41), and a relay apparatus (30). The robot (10) performs work based on an operation command. The operation apparatus (21) detects and outputs an operator-operating force applied by the operator. The learning control section (41) outputs a calculation operating force. The relay apparatus (30) outputs the operation command based on the operator-operating force and the calculation operating force. The learning control section (41) estimates and outputs the calculation operating force by using a model constructed by performing the machine learning of the operator-operating force, the surrounding environment data, the operation data, and the operation command based on the operation data and the surrounding environment data outputted by the sensors (11 to 13), and the operation command outputted by the relay apparatus (30).

Abstract: 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.