Performance Metrics and Test Methods for Robotic Hands

The goal of this study was to use a pressure sensor to measure the force distribution and contact area of the hand when gripping, pushing, and pulling a cylinder. Data was collected from 10 subjects with no hand impairments and from 1 subject with rheumatoid arthritis (RA). Subjects grasped an aluminum cylinder wrapped with a Tekscan pressure sensor and performed each trial at 25%, 50%, and 100% maximum voluntary exertion. A relationship was found between increasing exertion and increasing hand area with increasing hand contact area. The force distribution maps showed the thenar region of the hand exerts the most force during pushing while the metacarpal joint line exerts the highest force during pulling. The third and fourth phalange were found to exert the highest phalange force during gripping. The force distribution maps from the RA subject showed higher thumb forces and distal phalange forces, relative to the entire phalange, compared to the non-impaired subjects. This suggests that the RA subject compensates for the lack of phalange function with the regions of the hand that still function. Future studies should sample individuals with a larger hand area range and sample more individuals with RA.

In this paper, we present a novel strategy to detect the slipping of an object grasped by a human hand. The recognition of slipping of a grasped object early plays a significant role in designing the dexterous robotic hands to ensure a firm grasping. Here, we present a system that uses force sensors embedded in a tight glove to capture force variations during a slipping of a grasped object. The analysis of contribution by five fingers and the palm for grasping is presented based on new factor called contribution factor. Also, we propose a new direction to incorporate controlling of dexterous robot hands based on spatial activity of force exerted by hand to ensure a firm grasping.

A device that provides quantitative assessment of the grasping function and allows grasping function improvements to be monitored over time can potentially be very useful for hand surgeons, physiotherapists and occupational therapists. A Dynamic Grasping Assessment System (DGAS) that is capable of measuring finger forces during wrist extension, flexion, adduction and abduction was developed. The DGAS can measure forces for each individual finger in the range from 0 to 125 N with accuracy of ± 0.5 N, and can measure the wrist extension/flexion angle and the wrist ulnar/radial abduction angle with an accuracy of ± 0.25 deg. Furthermore the DGAS is capable of generating resistive torque during the wrist motion and allows to assess finger forces during wrist motion against resistive load. The DGAS can provide the following data: (1) finger forces as a function of time, wrist angle, wrist angular velocity and resistive load; (2) statistical analysis of the recorded finger force data;

Journal of Occupational Rehabilitation, 2000

The ability to accurately estimate grip force requirements may be important in exposure assessment, determining fitness for duty, or setting rehabilitation goals. This study investigates the effects of learning and experience, measurement system, and the nature of the task on grip force estimate accuracy. The grip forces applied during "pure" power grip tasks and simulated meat cutting tasks conducted in the laboratory, and during meat cutting operations at meat packing plants were measured with an instrumented tool handle. Estimates were recorded using the tool handle and a modified hand dynamometer. The results indicate that estimate accuracy varied greatly from individual to individual. No significant effect of learning on estimate accuracy was observed. The result of the meat cutting simulation and field study suggest that the force distribution at the hand-tool interface can markedly affect estimates. Great care must be taken in the collection of grip force estimates, as well as in the interpretation of the data. Improved understanding of the factors affecting estimates of grip force requirements should aid in the interpretation of functional capacity evaluations, and in the establishment of goals for rehabilitation.

[Proceedings] 1992 IEEE International Conference on Systems, Man, and Cybernetics

The Compliance Center concept formulated earlier for robotic grippers [24,25] was recently extended to multifingered robotic grasps [3,16,17] in quasistatic situations. A recent work [21] further extended the concept to grasps in dynamic situations and termed the reformulated concept as the Grasp Admittance Center. It also showed that a grasp with an admittance center will have 4 distinct advantagesstability, decoupled force/motion relation, decoupled time response and the ease of assigning the grasp dynamic behavior. Of the four advantages, conceptualizing the decoupled time response is difficult while the remaining 3 advantages are e d y comprehendable. In view of this, the present work describes experiments wherein a carefully built passive compliant device emulates the dynamic behavior of multifingered grasps. The device is used to demonstrate the change in the time-response of 3 types of grasps: (i) a grasp in a general situation, (ii) a grasp with a compliance center only, and (iii) a grasp with an admittance center. The experimental results (photographic records) of the timeresponse of the 3 grasps clearly indicate the directionally decoupled dynamic behavior of an admittance center grasp, and the absence of such a behavior in general grasps and in grasps with a compliance center only. Such decoupled behavior is highly desirable in tasks involving constrained manipulation of delicate objects.

2018

This force-feedback approach compares the effect on the sensing ability through a worn glove of the force application of an i-Limb Ultra robotic hand for several experimental scenarios. A Takktile sensor was integrated into a fabricated fingertip to measure the applied force of the i-Limb Ultra. A controller was then designed using MATLAB/Simulink to manipulate the finger motion of the i-Limb to apply force to an external load cell. Testing was performed to check the force measurements and sensing ability/quality for two cases: hand with no glove and hand with a nitrile glove. Each of these scenarios were tested by applying fingertip force in 3 different modes: open/close with no contact, continuous tapping and constant force.

Journal of Medical Engineering & Technology, 2001

We developed an instrumented object for quantitative evaluation of functional tasks performed with lateral hand grasp. The device was instrumented with three force transducers based on metal foil strain gauges. The transducers allowed simultaneous monitoring of the grasp force, the perpendicular force at the tip, and the force in the long axis of the instrumented object. The device was used for evaluation of a simulated eating task performed by able-bodied subjects and a tetraplegic subject instrumented with an FES hand grasp system. Use of the instrumented object will allow us to gain a more thorough understanding of the application of forces on a tool during important functional tasks of daily living. This knowledge will be used to improve the control of a closed-loop FES hand grasp system incorporating natural sensory feedback.

International Journal of Engineering Research and, 2019

The focus of this work was the realization of a prototype of a robotic hand, with the ability to mimic the movements of the human hand, and determine the force exerted by manipulating different electronic elements. To carry out the process of elaboration, it developed in the SOLIDWORKS program the design of each part of hand (fingers, wrist and palm), taking into account the movements it can make, later with the help of a 3D printer and the CURA program, each designed part in SOLIDWORKS was printed to be assembled and the prototype of a human hand was obtained. To achieve the operation of this prototype, ARDUINO programming software was used, that allowed to control the movement of the prototype by interacting with the human hand through the use of a glove with the implementation of flexo sensors on each of his fingers in such a way that the prototype could mimic the different movements that the human hand exerts, with the use of this glove. Force sensors were subsequently implemented on each of the fingers of the prototype, so that they could determine the force exerted on each of these when manipulating different objects. Finally, the prototype of the robotic hand was physically obtained, with the ability to manipulate objects and determine the force exerted on each of your fingers.

Advanced Robotics, 2006

A novel approach for evaluation of a grasp in humans is presented. The key novelty is combination of a haptic interface with force/torque transducers for measuring the grasp force. This paper presents results of grasp and load force coordination for quasi-static and dynamic external load force disturbances for a power grasp. An elevation of the grasp force is observed in a dynamic task. Elevation of the grasp force is needed for an additional safety margin to ensure a stable grasp.

Ergonomics, 2016