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 device for automatically hand-swaying beverage cups is disclosed, comprising a robotic arm and a cover, wherein the robotic arm has a plurality of movable arms and a plurality of joints that pivotally connect each of the movable arms to each other, and at the extreme end of such movable arms there install a pair of symmetrical clamping components and a clamping controller, and also includes a host computer electrically connected to each of the movable arms, each of the joints and the clamping controller, respectively; in addition, the cover respectively has a conical surface on the outside, an inner hole is openly configured on the bottom surface of the cover, and each of the clamping components can collectively clamp the cover and the cup thus facilitating the hand-swaying operations of the cup with the robotic arm.

An object manipulation apparatus according to an embodiment of the present disclosure includes a memory and a hardware processor coupled to the memory. The hardware processor is configured to: calculate, based on an image in which one or more objects to be grasped are contained, an evaluation value of a first behavior manner of grasping the one or more objects; generate information representing a second behavior manner based on the image and a plurality of evaluation values of the first behavior manner; and control actuation of grasping the object to be grasped in accordance with the information being generated.

A system and method for determining a misdetection of an object and subsequent response is disclosed. A robotic system may use a motion plan, which is derived based on an initial detection result of a package, to transfer the package from a start location to a task location. During implementation of the motion plan, the robotic system may obtain additional sensor data, which can be used to deviate from the initial motion plan and implement a replacement motion plan to transfer the package to the task location.

This patent proposal document provides a complete robot hand control scheme using myoelectric intention estimation of the human being using the kernel Principal Component Analysis Algorithm (kPCA). The robot hand system includes a biometric EMG sensor system, a robot hand including with multiple fingers, a controller connected with the biometric EMG sensor system, and a robot hand. The controller acquires the biometric EMG signal by means of a biometric sensor system, estimates myoelectric motion intention by applying the kernel principal component analysis (kPCA) algorithm using a kernel function, and delivers a control command corresponding to the estimated motion intention of the user to the robot hand.

Systems and methods for AI assisted reconfigurable, fixtureless manufacturing is disclosed. The invention eliminates geometry-setting tools (hard points, pins and nets—traditionally known as 3-2-1 fixturing schemes) and to replace the physical geometry setting with virtual datums driven by learning AI algorithms. A first type of part and a second type of part may be located by a machine vision system and moved by material handling devices and robots to locations within an assembly area. The parts may be aligned with one another and the alignment may be checked by the machine vision system which is configured to locate datums, in the form of features, of the parts and compare such datums to stored virtual datums. The parts may be joined while being held by the material handling devices or robots to form a subassembly in a fixtureless fashion. The material handling devices are able to grasp a number of different types of parts so that a number of different types of subassemblies are capable of being assembled. The system enables one skilled in the art to develop a product design with self-locating parts that will eliminate and minimize the need for geometry setting dedicated line tools and fixtures. This leads to the development of a manufacturing process that utilizes the industry 4.0 technologies to once again eliminate or significantly reduces the need for geometry setting line tools.

One or more embodiments of the present disclosure relate generally to the field of robotic grasping systems, and in particular to an active robotic manipulator that includes a passive grasping component so that the robotic manipulator can grasp a wide variety of objects and simultaneously provide soft grasping features which reduce the risk of damage to objects.

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.

In at least one embodiment, a system determines a set of possible grasp poses that allow a robot to successfully grasp an object by generating a set of potential grasp poses, and then evaluating the performance of each potential grasp pose. In at least one embodiment, the system performs a refinement operation on the grasp poses, and based on an evaluation of the poses, creates an improved set of possible grasps for the object.

A slide imaging apparatus includes: at least one imaging device configured to generate an image of a sample mounted on a slide, wherein the imaging device comprises an operating button; a storage device loadable with a plurality of slides and configured to store the slides; and a supply device configured to supply the slides from the storage device to the imaging device, wherein the supply device is configured to press the operating button.