Abstract: A system, for planning a grasp for implementation by a grasping device having multiple grasping members, including a processor and a computer-readable storage device having stored thereon computer-executable instructions that, when executed by the processor, cause the processor to perform multiple operations. The operations include generating, for each of the multiple grasping members, multiple planar polygon representations of a three-dimensional object model. The operations also include transforming a planar polygon, of the multiple polygons generated, to a frame of a link of multiple links of a subject member of the multiple grasping members, forming a transformed polygon, being a cross-section of the object model taken along a member-curling plane of the subject member. The operations further include sweeping, in iterations associated respectively with each link of the subject member, the link from a fully-open position for the link to a point at which the link contacts the transformed planar polygon.

Abstract: A method of determining an optimal grasp pose of an object by an end-effector of a robot in the execution of a task includes receiving a set of inputs via a controller, including a descriptive parameter of the object, a task wrench having a frame of reference, and a commanded end-effector grasp force. The method includes calculating a grasp wrench in the frame of reference of the task wrench, rotating and shifting the grasp pose, and then computing a resultant new grasp wrench via the controller until the task wrench and the grasp wrench are optimally balanced. Additionally, the method includes recording the optimal grasp pose as the grasp pose at which the grasp and task wrenches are optimally balanced, and then executing a control action via the controller using the recorded optimal grasp pose. A robotic system includes the robot and a controller programmed to execute the method.

Abstract: A method of determining an optimal grasp pose of an object by an end-effector of a robot in the execution of a task includes receiving a set of inputs via a controller, including a descriptive parameter of the object, a task wrench having a frame of reference, and a commanded end-effector grasp force. The method includes calculating a grasp wrench in the frame of reference of the task wrench, rotating and shifting the grasp pose, and then computing a resultant new grasp wrench via the controller until the task wrench and the grasp wrench are optimally balanced. Additionally, the method includes recording the optimal grasp pose as the grasp pose at which the grasp and task wrenches are optimally balanced, and then executing a control action via the controller using the recorded optimal grasp pose. A robotic system includes the robot and a controller programmed to execute the method.

Abstract: A system including a memory having instructions causing a processor to perform operations, for planning a grasping-device approach to an object by a grasping device, a pre-grasp device position, and a pre-grasp device pose. The operations comprise obtaining input data including grasping-device data, object data, and environmental-constraint data, determining, based on the grasping-device data, a grasp volume model, determining a test approach vector, and determining, using the vector, the constraint data, and the model, whether approach vector modification is needed. The operations also include modifying, if modification is needed, the test approach, yielding a resulting approach vector, and determining, if modification is not needed, that the test approach is the resulting approach vector.

Abstract: A system including a memory having instructions causing a processor to perform operations, for planning a grasping-device approach to an object by a grasping device, a pre-grasp device position, and a pre-grasp device pose. The operations comprise obtaining input data including grasping-device data, object data, and environmental-constraint data, determining, based on the grasping-device data, a grasp volume model, determining a test approach vector, and determining, using the vector, the constraint data, and the model, whether approach vector modification is needed. The operations also include modifying, if modification is needed, the test approach, yielding a resulting approach vector, and determining, if modification is not needed, that the test approach is the resulting approach vector.

Abstract: A system, for planning a grasp for implementation by a grasping device having multiple grasping members, comprising a processor and a computer-readable storage device having stored thereon computer-executable instructions that, when executed by the processor, cause the processor to perform multiple operations. The operations include generating, for each of the multiple grasping members, multiple planar polygon representations of a three-dimensional object model. The operations also include transforming a planar polygon, of the multiple polygons generated, to a frame of a link of multiple links of a subject member of the multiple grasping members, forming a transformed polygon, being a cross-section of the object model taken along a member-curling plane of the subject member. The operations further include sweeping, in iterations associated respectively with each link of the subject member, the link from a fully-open position for the link to a point at which the link contacts the transformed planar polygon.