A component mounting system includes a head to revolve multiple suction nozzles in a circumferential direction, a lifting and lowering device configured to lift and lower a suction nozzle at a predetermined revolving position, a storage device configured to store any one of multiple pieces of directionality information in association with identification information of the suction nozzle, and a control device configured to acquire corresponding directionality information from the storage device based on the acquired identification information of the suction nozzle and to perform pickup of the component supplied from the component supply device at the spinning position in accordance with the directionality information.

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.

This disclosure relates to a technology for grasping an object while adjusting a grasping force according to stiffness of the object measured by a tactile sensor module, especially to a robot-hand, which includes a tactile sensor module for measuring a normal force applied when grasping an object, a phalange sensor module having an actuator to generate a driving force and configured to measure a rotational displacement of a motor, and a hand back control unit for operating the actuator by generating a desired displacement signal to control a grasping force so that a grasping motion is stably and accurately achieved by applying a minimum grasping force to soft object with no sliding and minimized deformation, wherein the desired displacement signal is generated based on stiffness which is calculated from the normal force data and the rotational displacement data.

A robotic control system directs a robot to take an object from a human grasp by obtaining an image of a human hand holding an object, estimating the pose of the human hand and the object, and determining a grasp pose for the robot that will not interfere with the human hand. In at least one example, a depth camera is used to obtain a point cloud of the human hand holding the object. The point cloud is provided to a deep network that is trained to generate a grasp pose for a robotic gripper that can take the object from the human's hand without pinching or touching the human's fingers.

Systems and methods relating to an end-of-arm-tool that can be used in connection with the automated handling of vehicles, such as unmanned aerial vehicles (UAV), are disclosed. The described systems and methods can include an end-of-arm-tool which may include a load cell coupled to an end effector, such that forces and torques exerted on the end effector are translated onto the load cell. The measurement of forces and torques exerted on the end effector can facilitate determining various information in connection with the aerial vehicle, such as inertial properties or parameters associated with the aerial vehicle, the quality of the engagement between the end effector and the aerial vehicle, as well as diagnostic information in connection with the aerial vehicle. Additionally, the use of a load cell to measure forces and torques exerted on the end effector can eliminate the need to utilize traditional contact sensors typically required on the contact surfaces of an end-of-arm tool.

An object recognition system includes: an image capture system for capturing at least one image of an object, and for providing image data representative of the captured image; a patch identification system in communication with the image capture system for receiving the image data, and for identifying at least one image patch associated with the captured image, each image patch being associated with a potential grasp location on the object, each potential grasp location being described as an area that may be associated with a contact portion of an end effector of a programmable motion device; a feature identification system for capturing at least one feature of each image patch, for accessing feature image data in the database and for providing feature identification data responsive to the image feature comparison data; and an object identification system for providing object identify data responsive to the image feature comparison data.

A method for teaching a robot to perform an operation based on human demonstration using force and vision sensors. The method includes a vision sensor to detect position and pose of both the human's hand and optionally a workpiece during teaching of an operation such as pick, move and place. The force sensor, located either beneath the workpiece or on a tool, is used to detect force information. Data from the vision and force sensors, along with other optional inputs, are used to teach both motions and state change logic for the operation being taught. Several techniques are disclosed for determining state change logic, such as the transition from approaching to grasping. Techniques for improving motion programming to remove extraneous motions by the hand are also disclosed. Robot programming commands are then generated from the hand position and orientation data, along with the state transitions.

A robotic grasp generation technique for machine tending applications. Part and gripper geometry are provided as inputs, typically from CAD files. Gripper kinematics are also defined as an input. Preferred and prohibited grasp locations on the part may also be defined as inputs, to ensure that the computed grasp candidates enable the robot to load the part into a machining station such that the machining station can grasp a particular location on the part. An optimization solver is used to compute a quality grasp with stable surface contact between the part and the gripper, with no interference between the gripper and the part, and allowing for the preferred and prohibited grasp locations which were defined as inputs. All surfaces of the gripper fingers are considered for grasping and collision avoidance. A loop with random initialization is used to automatically compute many hundreds of diverse grasps for the part.

A film peeling apparatus for peeling a film from an object includes a peeling module including a first frame, a second frame connected to the first frame and including a rotation body and a gripper which grips the film attached to the object and to be removed from the object, and is rotatable about a rotation axis of the rotation body connecting the first frame and the gripper, and a third frame defining a boundary at which the film to be removed is peeled from the object, and an articulated robot including an articulated arm connected to the first frame.

Disclosed herein is a collection tool configured to independently grasp and cut a tether of a target object for removal from an environment. The collection tool may include a body securable to a robotic arm of a collection robot, a base secured to the body, a plurality of fingers having proximal ends attached to the base, the plurality of fingers constructed and arranged to grasp the target object at distal ends of the plurality of fingers, and a blade coupled to one of the base or body and configured to cut the tether to which the target object is attached while the target object is held by the plurality of fingers.