Apparatuses, systems, and techniques to place one or more objects in a location and orientation. In at least one embodiment, one or more circuits are to use one or more neural networks to cause one or more autonomous devices to place one or more objects in a location and orientation based, at least in part, on one or more images of the location and orientation.

Apparatuses, systems, and techniques to place one or more objects in a location and orientation. In at least one embodiment, one or more circuits are to use one or more neural networks to cause one or more autonomous devices to place one or more objects in a location and orientation based, at least in part, on one or more images of the location and orientation.

A computer-controlled robotic arm performs operations upon a workpiece, such as a knife with a blade that requires sharpening, by a set of one or more workstations, such as a grinder and a polisher. A position target having a defined surface profile is attached to the robot arm and scanned by a profilometer to determine a relative position of the arm with respect to a target centerpoint feature. The arm is then used to manipulate the centerpoint feature to locate operating features, such as a grinder's grinding surface, of the various workstations in the robot arm's coordinate system. A workpiece grasped by the robot arm is then scanned along with the target or another target to locate and profile the workpiece relative to the target. Based on the determined profile and positional relationships, the robot arm manipulates the workpieces so as to be operated upon by the workstations.

A clutch mechanism includes a spool that is configured to receive a cable, a disk with elasticity, a mechanism configured for locking and unlocking the movement of the disk, and at least one sensor. The at least one sensor being configured to measure the movement of at least one of the disk and the spool in the unlocked mode and to measure the movement of the spool relative to the disk when in a locked mode.

An autonomous control system includes an acquirer configured to acquire state data of a robot, visual data of the robot, and tactile data of the robot and a processor configured to decide on an action of the robot capable of accomplishing a task given to the robot on the basis of the state data, the visual data, and the tactile data. The processor generates first compressed data having a smaller number of dimensions than data obtained by combining the visual data and the tactile data by fusing and dimensionally compressing the visual data and the tactile data. The processor generates second compressed data having a smaller number of dimensions than the tactile data by dimensionally compressing the tactile data. The processor decides on the action on the basis of combined state data obtained by combining the state data, the first compressed data, and the second compressed data into one.

A computing device is configured to receive information representing an electronic drawing. The information is processed to locate and access the electronic drawing. Moreover, a template configuration file is accessed that corresponds with a category of the electronic drawing. Using the template configuration file, the at least one computing device can generate an item specification that includes information representing items to be reviewed for compliance with at least one rule. For each respective one of the items in the item specification, the respective item is determined to be present in the electronic drawing and complies with at least one rule identified in the template configuration file. Further, information is generated representing whether the respective item is present in the electronic drawing and complies with at least one rule identified in the template configuration file. The generated information is transmitted to at least one computing device.

A computing device is configured to receive information representing an electronic drawing. The information is processed to locate and access the electronic drawing. Moreover, a template configuration file is accessed that corresponds with a category of the electronic drawing. Using the template configuration file, the at least one computing device can generate an item specification that includes information representing items to be reviewed for compliance with at least one rule. For each respective one of the items in the item specification, the respective item is determined to be present in the electronic drawing and complies with at least one rule identified in the template configuration file. Further, information is generated representing whether the respective item is present in the electronic drawing and complies with at least one rule identified in the template configuration file. The generated information is transmitted to at least one computing device.

An end effector adaptor device for a robotic arm may have a body adapted to be secured to a working end of a robotic arm at a proximal face, the body having a distal face configured for connection of an end effector thereto. A proximal connector is in the proximal face, the proximal connector configured to be connected to a complementary connector at the working end of the robotic arm for signal and power transmission between the robotic arm and the body. A distal connector is in the distal face, the distal connector configured to be connected to a complementary connector at the end effector connected to the distal face for signal transmission and/or power transmission between the body and the end effector. Circuitry is between the proximal connector and the distal connector.

A robot system includes a robot configured to operate in cooperation with a person, a specifying section configured to specify a person present in a region at a predetermined distance from the robot, and a control section configured to decelerate or stop the operation of the robot when the presence of the person in the region is specified by the specifying section. The control section changes the distance based on a result of specifying the person by the specifying section.

An intelligent robot cleaner setting a travel path based on a video learning includes a travel driver, a suction unit, an image acquisition unit, and a controller. The travel driver moves to an area to be cleaned along the travel path. The suction unit sucks foreign substances on the travel path. The image acquisition unit acquires an image on the travel path. The controller analyzes the image, decides whether an object is present on the travel path, classifies a type of the object, and sets a bypass travel path that avoids the object if the object is an avoidance object.