Data-driven optimization for underactuated robotic hands

Passively adaptive and underactuated robotic hands have shown the potential to achieve reliable grasping in unstructured environments without expensive mechanisms or sensors. Instead of complex run-time algorithms, such hands use design-time analysis to improve performance for a wide range of tasks. Along these directions, we present an optimization framework for underactuated compliant hands. Our approach uses a pre-defined set of grasps in a quasistatic equilibrium formulation to compute the actuation mechanism design parameters that provide optimal performance. We apply our method to a class of tendon-actuated hands; for the simplified design of a two-fingered gripper, we show how a global optimum for the design optimization problem can be computed. We have implemented the results of this analysis in the construction of a gripper prototype, capable of a wide range of grasping tasks over a variety of objects

Advancing the Underactuated Grasping Capabilities of Single Actuator Prosthetic Hands

The last decade has seen significant advancements in upper limb prosthetics, specifically in the myoelectric control and powered prosthetic hand fields, leading to more active and social lifestyles for the upper limb amputee community. Notwithstanding the improvements in complexity and control of myoelectric prosthetic hands, grasping still remains one of the greatest challenges in robotics. Upper-limb amputees continue to prefer more antiquated body-powered or powered hook terminal devices that are favored for their control simplicity, lightweight and low cost; however, these devices are nominally unsightly and lack in grasp variety. The varying drawbacks of both complex myoelectric and simple body-powered devices have led to low adoption rates for all upper limb prostheses by amputees, which includes 35% pediatric and 23% adult rejection for complex devices and 45% pediatric and 26% adult rejection for body-powered devices [1]. My research focuses on progressing the grasping capabilities of prosthetic hands driven by simple control and a single motor, to combine the dexterous functionality of the more complex hands with the intuitive control of the more simplistic body-powered devices with the goal of helping upper limb amputees return to more active and social lifestyles. Optimization of a prosthetic hand driven by a single actuator requires the optimization of many facets of the hand. This includes optimization of the finger kinematics, underactuated mechanisms, geometry, materials and performance when completing activities of daily living. In my dissertation, I will present chapters dedicated to improving these subsystems of single actuator prosthetic hands to better replicate human hand function from simple control. First, I will present a framework created to optimize precision grasping – which is nominally unstable in underactuated configurations – from a single actuator. I will then present several novel mechanisms that allow a single actuator to map to higher degree of freedom motion and multiple commonly used grasp types. I will then discuss how fingerpad geometry and materials can better grasp acquisition and frictional properties within the hand while also providing a method of fabricating lightweight custom prostheses. Last, I will analyze the results of several human subject testing studies to evaluate the optimized hands performance on activities of daily living and compared to other commercially available prosthesis

Grasp planning for a reconfigurable parallel robot with an underactuated arm structure

In this paper, a novel approach of grasp planning is applied to find out the appropriate grasp points for a reconfigurable parallel robot called PARAGRIP (Parallel Gripping). This new handling system is able to manipulate objects in the six-dimensional Cartesian space by several robotic arms using only six actuated joints. After grasping, the contact elements at the end of the underactuated arm mechanisms are connected to the object which forms a closed loop mechanism similar to the architecture of parallel manipulators. As the mounting and grasp points of the arms can easily be changed, the manipulator can be reconfigured to match the user's preferences and needs. This paper raises the question, how and where these grasp points are to be placed on the object to perform well for a certain manipulation task. <br><br> <i>This paper was presented at the IFToMM/ASME International Workshop on Underactuated Grasping (UG2010), 19 August 2010, Montréal, Canada.</i&gt

Whole-Hand Robotic Manipulation with Rolling, Sliding, and Caging

Traditional manipulation planning and modeling relies on strong assumptions about contact. Specifically, it is common to assume that contacts are fixed and do not slide. This assumption ensures that objects are stably grasped during every step of the manipulation, to avoid ejection. However, this assumption limits achievable manipulation to the feasible motion of the closed-loop kinematic chains formed by the object and fingers. To improve manipulation capability, it has been shown that relaxing contact constraints and allowing sliding can enhance dexterity. But in order to safely manipulate with shifting contacts, other safeguards must be used to protect against ejection. “Caging manipulation,” in which the object is geometrically trapped by the fingers, can be employed to guarantee that an object never leaves the hand, regardless of constantly changing contact conditions. Mechanical compliance and underactuated joint coupling, or carefully chosen design parameters, can be used to passively create a caging grasp – protecting against accidental ejection – while simultaneously manipulating with all parts of the hand. And with passive ejection avoidance, hand control schemes can be made very simple, while still accomplishing manipulation. In place of complex control, better design can be used to improve manipulation capability—by making smart choices about parameters such as phalanx length, joint stiffness, joint coupling schemes, finger frictional properties, and actuator mode of operation. I will present an approach for modeling fully actuated and underactuated whole-hand-manipulation with shifting contacts, show results demonstrating the relationship between design parameters and manipulation metrics, and show how this can produce highly dexterous manipulators