Human in-hand dexterity can be highly fluid and unstructured, with multiple phalanxes breaking and re-establishing contact during any given task. In contrast, prevailing research in robotic manipulation has focused on highly structured well-controlled motions, where contact points are carefully characterized. Maintaining grasp stability by satisfying traditional closure conditions during complex within-hand manipulation motions can be difficult, even with highly articulated end effectors. However, simple grippers can still achieve an effective range of in-hand manipulation tasks without strict closure conditions, as long as the object can be bounded locally relative to the hand frame. The end effector can be considered as a tool to limit the range of possible object poses. In particular, the energy of the hand-object system can be used to determine an attractor region toward which the hand drives the object. This can be combined with a sparse sampling of the configuration space to find a set of manipulation primitives that can reliably constrain the object inside the hand workspace even without feedback, a strategy proposed as whole-hand caging manipulation. In this paper, experimental results with a planar underactuated gripper are presented to validate this manipulation strategy, and it is shown that even though contacts are regularly broken and reformed, the object can be reliably manipulated within the hand workspace without ejection, and challenging movements such as sliding and gaiting can be reliably performed.

Human in-hand dexterity can be highly fluid and unstructured, but in contrast, prevailing research in robotic manipulation has focused on highly structured, well-controlled motions where contact points are carefully characterized. Maintaining grasp stability through traditional closure conditions during complex within-hand manipulation motions can be difficult, even with highly-articulated end-effectors. However, simple grippers can still achieve an effective range of in-hand manipulation tasks without strict closure conditions, as long as the object can be bounded locally relative to the hand frame. The end-effector can be utilized as a tool to limit the range of possible object poses. We show that the hand-object system's configuration space can be sampled to find a set of manipulation primitives that can reliably constrain the object inside the hand workspace even without feedback, a strategy proposed as whole-hand caging manipulation. Experimental results with a planar (gravity into the page), two-finger underactuated gripper (Yale OpenHand) are presented to validate this manipulation strategy, and it is shown that even though contacts are regularly broken and reformed, the object can be repeatability manipulated within the hand workspace without ejection, enabling challenging behaviors such as sliding and gaiting.

Performing dexterous manipulation of unknown objects with robot grippers without using high-fidelity contact sensors, active/sliding surfaces, or a priori workspace exploration is still an open problem in robot manipulation and a necessity for many robotics applications. In this paper we present a two-fingered gripper topology that enables an enhanced predefined in-hand manipulation primitive controlled without knowing the size, shape, or other particulars of the grasped object. The in-hand manipulation behavior, namely, the planar manipulation of the grasped body, is predefined thanks to a simple hybrid low-level control scheme and has an increased range of motion due to the introduction of an elastic pivot joint between the two fingers. Experimental results with a prototype clearly show the advantages and benefits of the proposed concept. Given the generality of the topology and in-hand manipulation principle, researchers and designers working on multiple areas of robotics can benefit from the findings.

Commercially available robotic hands are often expensive, customized for specific platforms, and difficult to modify. In this paper, we present the design of an open-source, low-cost, single actuator underactuated hand that can be created through fast and commonly-accessible rapid-prototyping techniques and simple, off-the-shelf components. This project establishes the design of an adaptive, four-finger hand utilizing simple 3D-printed components, compliant flexure joints, and readily obtainable off-the-shelf parts. Modular and adjustable finger designs are provided, giving the user a range of options depending on the intended use of the hand. The design tradeoffs and decisions made to achieve the 3D-printable, compact and lightweight robotic gripper are discussed, as well as a preliminary discussion of the performance differences between the finger designs. The authors intend this work to be the first in a series of open-source designs to be released, and through the contributions of the open-source user community, result in a large number of design modifications and variations available to researchers.

In this paper, we demonstrate an underactuated finger design and grasping method for precision grasping and manipulation of small objects. Taking inspiration from the human grasping strategy for picking up objects from a flat surface, we introduce the flip-and-pinch task, in which the hand picks up a thin object by flipping it into a stable configuration between two fingers. Despite the fact that finger motions are not fully constrained by the hand actuators, we demonstrate that the hand and fingers can interact with the table surface to produce a set of constraints that result in a repeatable quasi-static motion trajectory. Even when utilizing only open-loop kinematic playback, this approach is shown to be robust to variation in object size and hand position. Variation of up to 20° in orientation and 10 mm in hand height still result in experimental success rates of 80% or higher. These results suggest that the advantages of underactuated, adaptive robot hands can be carried over from basic grasping tasks to more dexterous tasks.

This video demonstrates the use of an underactuated robotic hand modified for the flip-and-pinch task to pick up thin objects from a table surface. Though well-suited for power-grasping, underactuated hands have difficulty with pinch-grasping and precision motions. We introduce a repeatable and robust method by which an underactuated hand flips thin objects off the table into a stable pinch grasp. We explain why this task is quasi-static and robust for a wide range of object dimensions.

In this paper we demonstrate an underactuated finger design and grasping method for precision grasping and manipulation of relatively small objects. Taking a cue from human manipulation, we introduce the flip-and-pinch task, in which the hand picks up thin objects from a table surface by flipping it into a stable configuration. Despite the fact that finger motions are not fully constrained by the hand actuators, we demonstrate that the hand and fingers can be configured with the table surface to produce a set of constraints that result in a repeatable quasi-static motion trajectory. This approach is shown to be robust for a variety of object sizes, even when utilizing identical open-loop kinematic playback. Experimental results suggest that the advantages of underactuated, adaptive robot hands can be carried over to dexterous, precision tasks as well.