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.

A robot for object manipulation may include sensors, a robot appendage, actuators configured to drive joints of the robot appendage, a planner, and a controller. Object path planning may include determining poses. Object trajectory optimization may include assigning a set of timestamps to the poses, optimizing a cost function which may be a cost function for finger sliding based on a penalty for a sliding distance, a change in desired normal direction, and a wrench error associated with sliding a robot finger, and generating an object trajectory based on the optimized cost function. Grasp sequence planning may be model-based or deep reinforcement learning (DRL) policy based. The controller may execute the object trajectory and the grasp sequence via the robot appendage and actuators.

A robot for object manipulation may include sensors, a robot appendage, actuators configured to drive joints of the robot appendage, a planner, and a controller. Object path planning may include determining poses. Object trajectory optimization may include assigning a set of timestamps to the poses, optimizing a cost function based on an inverse kinematic (IK) error, a difference between an estimated required wrench and an actual wrench, and a grasp efficiency, and generating a reference object trajectory based on the optimized cost function. Grasp sequence planning may be model-based or deep reinforcement learning (DRL) policy based. The controller may implement the reference object trajectory and the grasp sequence via the robot appendage and actuators.

In variants, a method for robot control can include: receiving sensor data of a scene, modeling the physical objects within the scene, determining a set of potential grasp configurations for grasping a physical object within the scene, determining a reach behavior based on the potential grasp configuration, determining a trajectory for the reach behavior, and grasping the object using the trajectory.

Robotic gripping devices and methods for performing a picking operation. The methods described herein may involve positioning a gripping device with respect to an item to be grasped and then executing a first picking operation using the gripping device to obtain a grasp on the item. The methods may then involve executing at least two of a force detection procedure to detect a force applied to a portion of the gripping device, a grasping space detection procedure to detect an item in grasping range of the gripping device, a pressure detection procedure configured to detect pressure in an airflow path, and an item load detection procedure to detect force in a mechanical load path of the gripping device.

The invention refers to the area of control of a limb device in the form of an artificial limb for a human or a robot limb. In particular, the invention is related to a control unit for electrically controlling an electrically controllable limb device, the limb device comprising a plurality of actuators, the control unit comprising a first interface for connecting the control unit to the limb device, the control unit comprising a second interface for connecting the control unit to a data gathering device comprising one or more sensing devices, the control unit comprising a processing unit which is arranged for controlling the limb device at least based on data gathered by the data gathering device, wherein the control unit is arranged for outputting one single control action step to the actuators of the limb device calculated by the processing unit based on a first data or data combination received from the data gathering device, and the control unit is arranged for outputting a plurality of control action steps to the actuators of the limb device calculated by the processing unit based on a second data or data combination received from the data gathering device, the second data or data combination being different from the first data or data combination, the plurality of control action steps inducing a more complex automatic movement of the limb device that the one single control action step. The invention further refers to a system comprising such a control unit, a method for controlling an electrically controllable limb device and a computer program.

The present disclosure relates to a control device, a control method, and a program capable of supporting an object with a more appropriate supporting force. The control device includes a supporting force control unit that controls a supporting force for supporting an object on the basis of information regarding a shape of a contact portion in contact with the object and information regarding a shear force of the contact portion. The information regarding the shear force includes, for example, information regarding a shear displacement of the contact portion. The present disclosure can be applied to, for example, a control device, a control method, an electronic device, a robot, a support system, a gripping system, a program, and the like.

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.

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.

This patent application relates to apparatus and methods for enhanced microelectronic device handling. Apparatus comprises a pick arm having a pick surface configured for receiving a microelectronic device thereon, drives for moving the pick arm and reorienting the pick surface in the X, Y and Z planes and about a horizontal rotational axis and a vertical rotational axis, and a sensor device carried by the pick arm and configured to detect at least one of at least one magnitude of force and at least one location of force applied between the pick surface and a structure contacted by the pick surface or a structure and a microelectronic device carried on the pick surface. Related methods are also disclosed.