An appearance inspection system enabling a route to be easily set when a target is imaged while causing a relative position of an imaging device with respect to the target to be different is provided. A decision part decides a plurality of relative position candidates of the imaging device with respect to the target at which focus of a lens module is possible on the inspection target position with regard to each of a plurality of the inspection target positions on the target. A selection part selects relative positions one by one from corresponding plurality of relative position candidates for each of the plurality of inspection target positions and selects a route candidate satisfying a preset requirement from a plurality of route candidates generated by sequentially connecting the plurality of selected relative positions as a designation route.

A robot system (2a . . . 2d) is specified, which comprises a robot (1a, 1b) having a gripping unit (4) for collecting and placing down/throwing goods (26a, . . . 26g), wherein the goods (26a, . . . 26g) are differentiated into multiple types with respect to their dimensional stability, compressive stability, flexural rigidity, strength, their absolute weight and/or specific weight. When the goods (26a, . . . 26g) are manipulated, the robot (1a, 1b) and/or the gripping unit (4) are controlled depending on the type determined for the goods (26a, . . . 26g). Moreover, a method for operating the robot system (2a, . . . 2d) is specified.

There is provided a system that includes a review tool configured to review at least part of potential defects of an examined object, and assign each of the at least part of the potential defects with a multiplicity of attribute values. The system also includes a computer-based classifier configured to classify, based on the attribute values as assigned, the at least part of potential defects into a set of classes, the set comprising at least a first major class, a second major class and a first minor class, the classifier trained based on a training set comprising a multiplicity of training defects with assigned attribute values, the training defects classified into the set of classes.

Systems, methods, and associated components for robotic manipulation of physical objects. The physical objects include three-dimensional gripping features configured to be detected by an optics system and gripped by an end-effector of a robotic arm with sufficient gripping force to move the physical objects against the force of gravity. Sets of the physical objects can have different sizes and shapes and, in some examples, include identically constructed three-dimensional gripping features.

Machine vision methods and systems determine if an object within a work field has one or more predetermined features. Methods comprise capturing image data of the work field, applying a filter to the image data, in which the filter comprises an aspect corresponding to a presumed feature, and based at least in part on the applying, determining if the object has the presumed feature. Systems comprise a camera system configured to capture image data of the work field, and a controller communicatively coupled to the camera system and programmed to apply a filter to the image data, and based at least in part on applying the filter, determine if the object has the specific feature. Robotic installation methods and systems that utilize machine vision methods and systems also are disclosed.

Machine vision methods and systems determine if an object within a work field has one or more predetermined features. Methods comprise capturing image data of the work field, applying a filter to the image data, in which the filter comprises an aspect corresponding to a specific feature, and based at least in part on the applying, determining if the object has the specific feature. Systems comprise a camera system configured to capture image data of the work field, and a controller communicatively coupled to the camera system and comprising non-transitory computer readable media having computer-readable instructions that, when executed, cause the controller to apply a filter to the image data, and based at least in part on applying the filter, determine if the object has the specific feature. Robotic installation methods and systems that utilize machine vision methods and systems also are disclosed.

There is provided a system that includes a review tool configured to review at least part of potential defects of an examined object, and assign each of the at least part of the potential defects with a multiplicity of attribute values. The system also includes a computer-based classifier configured to classify, based on the attribute values as assigned, the at least part of potential defects into a set of classes, the set comprising at least a first major class, a second major class and a first minor class, the classifier trained based on a training set comprising a multiplicity of training defects with assigned attribute values, the training defects classified into the set of classes.

In one embodiment, a method includes receiving, from a first sensor on a robot, first sensor data indicative of an environment of the robot. The method also includes identifying, based on the first sensor data, an object of an object type in the environment of the robot, where the object type is associated with a classifier that takes sensor data from a predetermined pose relative to the object as input. The method further includes causing the robot to position a second sensor on the robot at the predetermined pose relative to the object. The method additionally includes receiving, from the second sensor, second sensor data indicative of the object while the second sensor is positioned at the predetermined pose relative to the object. The method further includes determining, by inputting the second sensor data into the classifier, a property of the object.

Machine vision methods and systems determine if an object within a work field has one or more predetermined features. Methods comprise capturing image data of the work field, applying a filter to the image data, in which the filter comprises an aspect corresponding to a specific feature, and based at least in part on the applying, determining if the object has the specific feature. Systems comprise a camera system configured to capture image data of the work field, and a controller communicatively coupled to the camera system and comprising non-transitory computer readable media having computer-readable instructions that, when executed, cause the controller to apply a filter to the image data, and based at least in part on applying the filter, determine if the object has the specific feature. Robotic installation methods and systems that utilize machine vision methods and systems also are disclosed.

A robot control device is configured to perform, during movement of an end effector of a robot in a movement direction of a target object, force control by which a force acts on the target object based on an output of a force detection unit included in the robot to cause the robot to perform work on the target object by the end effector. Whether the work is able to be started is determined in a process where the end effector follows the movement of the target object, and when it is determined that the work is able to be started, the work is caused to start.