Accuracy in interference determination between a hand gripping a workpiece and nearby objects is increased. An information processing apparatus includes a measuring unit configured to decide an object to be gripped among a plurality of objects on the basis of a first image of the imaged objects, a specifying unit configured to specify an attention area for determining, when a gripping device grips the object to be gripped, whether the gripping device interferes with objects near the object to be gripped, a controller configured to change an imaging range of an imaging device on the basis of the attention area, and a determination unit configured to determine, when the gripping device grips the object to be gripped, whether the gripping device interferes with the objects near the object to be gripped on the basis of a second image of an object imaged in a changed imaging range.

A machine vision-based method and system for measuring 3D pose of a part or subassembly of parts having an unknown pose are disclosed. A number of different applications of the method and system are disclosed including applications which utilize a reprogrammable industrial automation machine such as a robot. The method includes providing a reference cloud of 3D voxels which represent a reference surface of a reference part or subassembly having a known reference pose. Using at least one 2D/3D hybrid sensor, a sample cloud of 3D voxels which represent a corresponding surface of a sample part or subassembly of the same type as the reference part or subassembly is acquired. The sample part or subassembly has an actual pose different from the reference pose. The voxels of the sample and reference clouds are processed utilizing a matching algorithm to determine the pose of the sample part or subassembly.

A device capable of acquiring a deviation of a working position of a tool with respect to a target position of a workpiece with higher accuracy in accordance with actual work. A device for acquiring a deviation amount of a working position of a tool with respect to a target position when a work is performed on a workpiece with respect to the target position by the tool, the tool being moved by a movement machine, the device including: a camera arranged in a predetermined positional relationship with respect to the tool and configured to image the target position at a first time point when the tool performs an operation for the work; and a deviation amount acquisition section configured to acquire a deviation amount between the working position and the target position at the first time point, based on a position of the target position in image data imaged by the camera and information indicating a position of the working position in the image data.

In general terms, the present invention provides a passively compliant robotic arm having one or more variable stiffness joints controllable by first and second bi-directional actuators that can be independently operated. Each bi-directional actuator may be operable in a first configuration to urge the joint in a first direction, and in a second configuration to urge the joint in a second direction opposite to the first direction. The bi-directional actuators may be operated in a cooperating mode (high torque mode) in which they work in tandem (i.e. both in the first configuration or second configuration) to double the available torque output. The bi-directional actuators may also (or alternatively) be operated in a high stiffness mode (antagonist mode) in which they counter-act each other by operating so that they oppose one another (i.e. one in the first configuration and the other in the second configuration). The high torque mode may be utilised for an initial portion of a movement trajectory, and the antagonist mode for a final portion of the movement trajectory. The relatively high stiffness in the high stiffness/antagonist mode results from the combined effects of the non-linear force-deflection relationship of the first and second resilient members. The resilient members may each comprise an elastic element, tendon or other resilient member that can be stretched (elongated) to increase tension therein and thereby urge the joint to move.

Provided are a measurement system, a measurement device, a measurement method, and a measurement program. 3D data is registered to 3D data based on the displacements of joints of a robot at a point in time when a 3D sensor measures 3D data of a measurement object at a specific measurement point while the robot is stopped, and the displacements of the joints of the robot at a point in time when the 3D sensor measures 3D data of the measurement object at a measurement point other than the specific measurement point while that robot is in motion. The 3D data is further registered to the 3D data such that a registration error between the 3D data and the 3D data is less than a threshold value. Similarly, each of 3D data is registered to the 3D data.

The seam welding apparatus includes a pair of rotating electrodes, an electrode supporting frame, a distance measuring means, and a controller. The electrode supporting frame supports the pair of rotating electrodes. The distance measuring means is provided on the electrode supporting frame and measures a distance to an edge of the steel plate. The controller controls the robot to adjust a running direction of the rotating electrodes so that a deviation comes into zero when a distance actually measured by the distance measuring means deviates from a predetermined distance. Thereby, it is accomplished that the seam welding apparatus is downsized as well as uninfluenced by the surface state and/or shape of workpiece (steel plate).

A grasping system includes a robotic arm having a gripper. A fixed sensor monitors a grasp area and an onboard sensor moves with the gripper also monitors the area. A controller receives information indicative of a position of an object to be grasped and operates the robotic arm to bring the gripper into a grasp position adjacent the object based on information provided by the fixed sensor. The controller is also programmed to operate the gripper to grasp the object in response to information provided by the first onboard sensor.

A safety system for safeguarding a machine is provided, said safety system having at least one safe sensor for producing safe data, wherein the safe sensor also produces non-safe data and/or a non-safe sensor for producing non-safe data is provided, wherein the safety system furthermore has a non-safe evaluation unit for processing the non-safe data and a safe evaluation unit that is configured to test the non-safe evaluation unit in that an evaluation result of the processing of the non-safe data is checked with reference to the safe data, The safe data have a lower accuracy and/or are more rarely available in comparison with the evaluation results.

An alignment system for an imaging sensor of a coordinate measuring machine incorporates a reference surface associated with a stage of the measuring machine but instead of imaging the reference surface as a location marker, the reference surface is incorporated into a combined imaging system together with the imaging sensor for imaging a feature associated with the imaging sensor. The imaged feature can be an internal part of the imaging sensor, such as an internal aperture, or an external feature in a fixed relationship with the imaging sensor, such as a lens hood.

A machine vision-based method and system for measuring 3D pose of a part or subassembly of parts having an unknown pose are disclosed. A number of different applications of the method and system are disclosed including applications which utilize a reprogrammable industrial automation machine such as a robot. The method includes providing a reference cloud of 3D voxels which represent a reference surface of a reference part or subassembly having a known reference pose. Using at least one 2D/3D hybrid sensor, a sample cloud of 3D voxels which represent a corresponding surface of a sample part or subassembly of the same type as the reference part or subassembly is acquired. The sample part or subassembly has an actual pose different from the reference pose. The voxels of the sample and reference clouds are processed utilizing a matching algorithm to determine the pose of the sample part or subassembly.