Unconventional Uses of Structural Compliance in Adaptive Hands

Che-Ming Chang1, Lucas Gerez1, Nathan Elangovan1, Agisilaos Zisimatos2, and Minas Liarokapis1

Abstract— Adaptive robot hands are typically created byintroducing structural compliance either in their joints (e.g.,implementation of flexure joints) or in their finger-pads. Inthis paper, we present a series of alternative uses of structuralcompliance for the development of simple, adaptive, compliantand/or under-actuated robot grippers and hands that canefficiently and robustly execute a variety of grasping anddexterous, in-hand manipulation tasks. The proposed designsutilize only one actuator per finger to control multiple degreesof freedom and they retain the superior grasping capabilities ofthe adaptive grasping mechanisms even under significant objectpose or other environmental uncertainties. More specifically, inthis work, we introduce, discuss, and evaluate: a) the conceptof compliance adjustable motions that can be predetermined bytuning the in-series compliance of the tendon routing systemand by appropriately selecting the imposed tendon loads, b)a design paradigm of pre-shaped, compliant robot fingers thatadapt / conform to the object geometry and, c) a hyper-adaptivefinger-pad design that maximizes the area of the contact patchesbetween the hand and the object, maximizing also graspstability. The proposed hands use mechanical adaptability tofacilitate and simplify the efficient execution of robust graspingand dexterous, in-hand manipulation tasks by design.

I. INTRODUCTION

Robotic end-effectors have evolved over the past fewdecades from simple, parallel jaw grippers to dexterous handsthat require complicated control laws and sophisticated sens-ing. The control of such devices is typically computationallyexpensive when performing versatile object manipulation andgrasping [1], [2]. By introducing elastic elements into tradi-tional robotic structures, the successful execution of robustgrasping tasks in unstructured environments can be achieved[3], [4]. Structural compliance is a key characteristic thatincreases grasp stability and conformability of the gripper/ hand to various object shapes. Early research focused oncreating flexible parallel jaw grippers that could conform tovarious objects [5] and more recent research explores appli-cations outside of industrial settings that involve interactionswith soft, biological materials [6]. Structural complianceincreases grasping robustness by allowing end-effectors tomaximize the contact patches between the gripper and theobject, dealing also with uncertainties in object positioningand surface geometries [7] and decreasesing the grasp forcerequired to extract stable grasps [8].

1 Che-Ming Chang, Lucas Gerez, Nathan Elangovan, and MinasLiarokapis are with the New Dexterity research team, Department ofMechanical Engineering, The University of Auckland, Auckland, NewZealand. Emails: ccha425@aucklanduni.ac.nz, lger871@aucklanduni.ac.nz,sela886@aucklanduni.ac.nz, minas.liarokapis@auckland.ac.nz

2 Agisilaos Zisimatos is with the Department of Electrical Engineer-ing, National Technical University of Athens, Athens, Greece. Email:el08087@mail.ntua.gr

Alternatively, structural compliance could also be usedfor in-hand manipulation. Traditionally, tendon driven un-deractuated systems have rigidly anchored tendons, andany attempt at increasing the tendon tension upon objectcontact would result in vast finger reconfiguration (change offinger configuration / pose). However, the use of non-rigidlyanchored tendons (in-series compliance) could facilitate theactuation of other mechanisms such as rotating finger padsor fingernail extensions for in hand manipulation or en-hancement of the grasping capacities. The compliance basedmechanical adjustment of the motion of these mechanismsdepends on the stiffness of the joints.

In this paper, we present alternatives uses of structuralcompliance for the development of adaptive robot grippersand hands and we evaluate the performance by such designapproaches for robust grasping and dexterous manipulation.More precisely, we propose a pre-shaped adaptive fingersparadigm and a hyper-adaptive finger-pads paradigm. Bothdesigns were developed in order to maximize the area ofcontact patches between the fingers and the grasped objects.This also maximizes specific grasp quality measures, ex-tracting more robust and stable grasps. The hyper-adaptivefinger-pads rely on a pins array design, similar to thedesign presented by [9]. With these simple elastic modules,high deformation and conformability to the object shapeis achieved. The multi-material pre-shaped finger designrelies on the combination of various elastic elements. Thepolyurethane core provides a stiffer backbone that increasesforce transmission while the pre-shaped curvature enhancescomformability to the object geometry. The silicone skinincreases the gripping capability of the device when graspingeveryday life objects. The pre-shaped finger design aims toincrease the total area of the contact patches during grasping.

Regarding dexterous, in-hand manipulation, we proposea two fingered adaptive robot hand that takes advantageof compliance adjustable manipulation motions. The handfingers are equipped with rotation and translation modules onthe distal phalanges of the fingers that facilitate the executionof local manipulation motions (rotation and translation).The timing of the triggering of the manipulation motionsdepends on the stiffness of the joints and is facilitated bythe introduction of in-series compliant elements in the tendonrouting system. All the proposed robot hands and grippers areunderactuated and of minimal cost, weight, and complexity.The efficiency of the proposed mechanisms is experimentallyvalidated with a variety of experimental paradigms involvingrobust grasping and dexterous manipulation with everydaylife objects. All designs will be made publicly available (inan open-source manner) to facilitate replication.

The rest of the document is organized as follows: Sec-tion II discusses the related work, Section III presents theemployed grasp quality measures, Section IV focuses on aseries of alternative uses of structural compliance and designsof adaptive robot hands, Section V presents the experimentsand the results, while Section VI concludes the paper.

II. RELATED WORK

Over the last decades, various designs of adaptive grippershave been proposed that facilitate the execution of robustgrasping and dexterous manipulation tasks. These designsexhibit some form of structural compliance and most of themare also underactuated. An underactuated design providessimplicity in operation and control and significantly reducesdevelopment cost as the number of motors is minimized.Significant research effort has also been put into investigatingalternative hand geometries and kinematics which led to non-conventional hand designs. There has been also significanteffort in making those hands freely available, using open-source dissemination and providing adequate documentationfor design replication [10]–[12].

Design approaches to implement structural compliance canroughly be categorized into two major approaches: adaptive,tendon-driven mechanism employing structural compliancein the joints and finger-pads levels and soft robotic mech-anisms using fully compliant structures and pneumatic orhydraulic actuation paradigms. Designs such as the YaleOpenHand project devices [1] use fingers with multipleelastic joints and soft finger-pads to increase their grip-ping capabilities and conformability to the shapes of thegrasped objects. Other designs such as the robot gripperfrom Robotiq’s adaptive gripper range [13], [14] or Festo’sadaptive finger gripper [15] employ serial elastic differentialtransmissions. Highly structural compliant soft continuumgrippers like the Versaball [16] from Empire Robotics, OceanOne’s soft grippers [17] or Soft Robotics’s soft gripper [18]are capable of grasping objects of various geometries by con-forming to the objects exterior hence increasing the numberof contact points. Limitations of such designs are usuallyobserved when manipulating very small or very soft objectswhere the membrane cannot form a stable contact [19].This trade-off between soft and rigid grippers outlined byHughes et al. describes the relationships between precision,structural compliance, DOF, and force exertion [20]. Softand continuum body manipulators benefit from high DOFand large deformation capacities. Comparatively, adaptive,tendon-driven mechanisms use less structural compliance,have better force exertion capabilities, and achieve higherprecision.

Traditionally, for the creation of adaptive, tendon drivenhands, structural compliance is introduced either in the joints(e.g., flexure joints) [2] or in their finger-pads [21], increasingthe mechanical adaptability and contact surface complianceof the overall grasping mechanism. Joint compliance inunderactuated designs allows grippers to grasp objects withunknown object poses using minimalistic control schemes.

III. GRASP QUALITY MEASURES

Task execution with a robotic hand is primarily dependenton the hand’s ability to constrain the object motion. Aneffective grasp is characterized by the ability of the handto withstand external disturbances while maintaining stableobject contact. In general, a hand can grasp a given object inmultiple ways. Quantifying the grasp quality is essential forthe optimization and selection of appropriate grasp types. Inthis study, we use the Grasp Wrench Space quality measureto quantify and visualize the effects of increased size of thecontact patches on the effectiveness of the grasp.

Fig. 1. Subfig. (a) presents an object O being grasped at contact pointsp1, p2, p3 using a patch contact model. The inset figure shows theadditional points with-in the patch that are being included, while subfig. (b)demonstrates that the grasp wrench space GWS′ generated by the contactpatch with additional points is significantly higher than the original GWS.

The torques applied at each one of the joints generate afinger force fi at the fingertip i. The force fi applied onthe object at a point pi generates a torque τi with respectto the object’s centre of mass. A wrench vector ωi is thecombination of these force and torque components definedas ωi = (fi, τi/ρ), where ρ is a constant used to define themetric of the wrench space [22]. A grasp G is defined as theset of all the points on the object surface that are in contactwith the fingers. Consider an object O as shown in Fig. 1that is being grasped by fingertips at the points p1, p2, p3. Apoint contact model provides the forces and twists acting ateach of these points. We adopt Coulomb’s friction model byapproximating the friction cone at the contact point pi by apyramid with m edges. The finger force fi exerted by thefinger i at this point can be expressed as a linear combinationof primitive forces fij , j = 1, ...,m along the pyramid edgesand wrench wi produced by fi at pi can be expressed as apositive linear combination of primitive wrenches wij . Thewrench produced by the n fingers can be calculated as,

W [G] =

n∑i=1

ωi =

n∑i=1

m∑j=1

αijωij

with αij ≥ 0,

n∑i=1

m∑j=1

αij ≤ 1

(1)

W [G] denotes the set of all wrenches associated withthe contact points of grasp G. The possible variations ofαij determines the set of possible resultant wrenches on theobject, which is the convex hull of the Minkowski sum of

Fig. 2. Single core Pre-Shaped Adaptive (PSA) robot fingers with rigidfingernails embedded in the elastomer material (left top). Example ofa parallel jaw gripper equipped with Multi-Segmented core Pre-ShapedAdaptive (MS-PSA) fingers with rubber skin and L shaped mounting bases(left bottom) and the 3D model of a parallel jaw gripper equipped withtwo MS-PSA fingers (right). The MS-PSA finger is composed of an innersegmented core, exterior silicone skin that has good gripping properties(high friction with plastic), a plastic fingertip, and a base. The segmentedcore provides anchors for the skin layer material to take the desired shapeand prevents layer peeling. The base and the fingertip have appropriatehollowed arches that provide mounting points for the elastic elements, usingthe concept of Hybrid Deposition Manufacturing (HDM) [23]. The mainsource of force transmission and compliance comes from the segmentedcore while the skin provides a higher friction coefficient with plastic duringthe execution of grasping tasks.

primitive wrenches ω. The set of all the wrenches that canbe applied to the object through the grasp G is called theGrasp Wrench Space (GWS). GWS is defined as the convexhull of the primitive wrenches of the contact points in G

GWS = ConvexHull(W [G]) (2)

The GWS can be described as the largest perturbationwrench the grasp can resist in any direction [24]. The higherthe volume of this grasp wrench space, the better the grasp.In order to visualize the effect of increased size of the contactpatches provided by the hyper adaptive fingers defined in thispaper, we calculate the GWS of patch contacts instead of thepoint contact model [25]. If the hand makes a patch contactcentered at point pi, the patch is defined as

P (i, r) = {z : δzi ≤ r, z ∈ O} (3)

where r ≥ 0 is the parameter that bounds the size of thepatch and δzi is the shortest edge between the points withindices i and z. This means that the point pz qualifies to bea member of a patch around pi if the distance between piand pz is less than or equal to r. The physical significance ofthis adapted quality measure is that a bigger contact patchwould provide a higher number of contact points therebysignificantly increasing the wrenches exerted on the objectand grasp quality (stability of grasp). Fig. 1 demonstrates theeffect of the additional wrenches exerted on the volume of theGrasp Wrench space. The new wrench space GWS′ formedusing patch contact is a superset of the GWS formed by thesingle point contacts. The compliance of the hands discussedin this paper, allows them to conform to the shape of the

objects being grasped thereby generating very large contactpatches and increased GWS. This ensures the stability of thegrasp and its ability to resist disturbances.

IV. DESIGNS INCORPORATING ALTERNATIVE USES OFSTRUCTURAL COMPLIANCE

In this section, we introduce three different designs em-ploying alternative uses of structural compliance for thedevelopment of adaptive robot hands.

A. Pre-Shaped Adaptive Robot Fingers

The Pre-Shaped Adaptive (PSA) finger is an elastic,compliant robot finger designed for maximizing the contactarea between the object and the finger during grasping. Theintroduction of a pre-shaped curvature is used to allow abetter conforming of the fingers around round and irregularobject shapes. Finger sizes and curvatures can be objectdependant and can vary significantly for objects of differentdimensions. Two types of PSA fingers were developed, asingle core PSA finger and a multi-segmented core version(MS-PSA), as shown in Fig. 2. Both fingers consist of aPMC-780 core with a PLA fingernail and a mounting base.To increase surface friction and the elastic conforming of thefinger, the MS-PSA finger is covered by a layer of Vytaflex-30. The five cavities in the PMC-780 core provide anchorsfor the Vytaflex-30 skin and act as segmented regions withdifferent elastic properties during reconfiguration for the MS-PSA finger. The bending of the finger allows it to conformto rectangular and non-round objects according to the forcesexerted on their surface. PSA robot fingers cannot fully resistshear forces, as they experience out of plane motions duringgrasping. Also, for small objects, it is more reliable to graspobjects within the elastic regions of the PSA finger to allowthe finger to conform to the object geometry. In Fig. 2,the PSA finger was mounted on a pivoting base of a twofingered pin joint based gripper while the MS-PSA fingerwas mounted on a rigid base of a parallel jaw gripper.

B. Hyper Adaptive Finger

Similarly to the pre-shaped robot fingers concept, themotivation for the development of the hyper-adaptive finger-pads comes from the desired maximization of the contactareas between the hand finger-pads and the object surface.This concept uses adaptive micro-structures that conform tothe object’s geometry in a “divide and conquer” mannerand constrains the object inside the grasp. The distributedforces across the finger pad during the grasp reconfigurationensure a stable grasp. It must be noted that the hyper-adaptivefinger-pads are compliant only in one direction and thus theyresist shear forces. This differs from traditional compliantstructures which deform equally in all directions, such asfoam, silicons, and other soft materials.

The Hyper Adaptive (HA) finger, shown in Fig. 4, iscomposed of pin array pads, acrylic plates, polymer springs,and plastic phalanges. The pin array pads consist of 48 pins(6x8 array) of 1.1 mm diameter made out of steel (eachfinger has two pin arrays). Each pin has a compliant rubbery

Fig. 3. Finger structures of the Compliance Adjustable Manipulation (CAM) gripper for the case of an extra rotation and translation degree of freedomlocated at the fingertip. An elastic band is connected in series with the tendon routing for both cases. For the rotation finger (left), the elastic band is wrappedaround a pulley connected with the ball bearing and the rotating part. For the translational finger (middle), the elastic band connects the moving part (thatmoves along appropriate slides) with the fingertip. A two-fingered CAM adaptive hand with a rotation module per fingertip (right). The development ofthe hand is based on the Hybrid Deposition Manufacturing (HDM) technique [23]. The base of the hand is the base of model T42 of the Yale OpenHandproject [10].

Fig. 4. The Hyper Adaptive (HA) finger consists of pin array pads (hyper-adaptive finger-pads), acrylic plates, polymer springs, and plastic phalangesthat support the pads. The pin array pads consist of 48 pins each. Each pinhas a compliant rubbery tip to increase the friction between the tip and theobject. The pins are mounted onto an acrylic guide plate that is connectedto the plastic phalanges. The compliance of the finger pads allows eachfinger to reconfigure to the exact object shape. The HA finger distributesthe contact forces to each pin, ensuring stability and robustness of the grasps.

tip made of Smooth-On PMC-780 that increases the frictionbetween the finger and the object. The pins are mounted ontoa 10 mm thick acrylic guide plate that is connected to theplastic phalanges. The acrylic plate is used to maintain atight tolerance between the plate and the pins, guaranteeingstable and unidirectional motion. In order to reduce weightand complexity of the system, traditional return springs werereplaced by an elastic polymer tube array made of Smooth-On Ecoflex 00-30. This design choice also reduces the finalcost and weight of the hyper adaptive finger. The complianceof the finger pads allows the finger to reconfigure to theobject shape. Doing so, the adaptive finger distributes thecontact forces to each pin, ensuring stability and robustnessat each grasp executed. The hyper adaptive fingers use atorsion spring at the pin joint and a flexure joint (made outof Smooth-On PMC-780) between the two phalanges of eachfinger. The finger pads and the fingers were designed to beeasily replaced if a different base or mount is needed. Inthe experiments, the gripper was tested using two differentbases: a base adapted from the Yale OpenHand Model T42[10] and a base of a parallel jaw gripper.

C. Compliance Based Adjustable Motions

The concept of compliance based adjustable manipula-tion motions focuses on introducing in-series compliancein the tendon routing system (see Fig. 3) that facilitatesthe execution of dexterous, in-hand manipulation tasks. TheCompliance Adjustable Manipulation (CAM) gripper designallows us to execute both grasping tasks (through simplefinger flexion) and dexterous, in-hand manipulation tasksemploying a single actuator per finger (for both cases). Thiswas done through displacement of an extra DoF the motionof which is affected by the tuning of the in-series compliance.

It must be noted that a careful selection of the jointstiffness and the in-series compliant elements can changethe tendon loads required to trigger the grasping and themanipulation motions and the timing of their triggering.Thus, the particular concept allows us to pre-adjust the handmotions by selecting the stiffness values of the compliantelements. The extra DoFs can facilitate the execution of avariety of dexterous manipulation tasks.

V. EXPERIMENTS AND RESULTS

In this section, we present the experiments that wereconducted in order to validate the efficiency of the proposedconcepts, designs, and grippers.

A. Robust Grasping

The experimental evaluation of the proposed hands andgrippers in grasping tasks focused on assessing the graspstability using objects from the YCB object set [26]. Aselection of eight daily objects from the YCB object setwere used in the experiments: a master chef can, a softball, a mustard bottle, a chain, a credit card, a fork, asmall cup, a jello box, a wooden cube, a plastic banana,a racquetball, and a marble. Individual objects were placedon a flat surface, and the grippers were attached to a robotarm (Universal Robots UR5) for grasping. For each object,the gripper/hand executes a grasp and the robot arm thenlifts the object. Then the object experiences disturbancesas the arm moves around in a predefined trajectory andfinally returns back to the initial configuration and placesthe object on the flat surface. Assessment of grasp stability

TABLE IGRASP STABILITY RESULTS COMPARISON. STABILITY IS ASSESSED AS THE ABILITY OF THE HAND / GRIPPER TO RETAIN A STABLE GRASP DURING

THE EXECUTION OF AN ARM TRAJECTORY THAT INTRODUCES SIGNIFICANT DISTURBANCES (AS SEEN IN THE VIDEO).

YCB objects

GrippersParallel jaw gripper Adaptive gripper

Sponge MSPSA HA HA T42Grasp Stability Grasp Stability Grasp Stability Grasp Stability Grasp Stability

Master chef can N* N* Y Y N* N* Y Y Y YSoft ball N* N* Y Y N* N* Y Y Y YMustard bottle Y Y Y Y Y Y Y Y Y YChain Y N Y Y Y Y Y Y Y YCredit card blank N N Y Y N N N N N NFork N N Y Y Y Y Y Y Y YSmall cup Y Y Y Y Y Y Y Y Y YJello box Y Y Y Y Y Y Y Y Y YWooden cube Y Y Y Y Y Y Y Y Y YPlastic banana Y N Y Y Y Y Y Y Y NRacquetball Y Y Y Y Y Y Y Y Y YMarble Y N Y Y Y Y Y Y Y Y

* grasps were not possible, as the object dimensions exceed the parallel jaw gripper aperture.

was based on the quality of the grasp. A successful, goodquality grasp experiences no notable object motion during thetask execution. In Fig. 5, we present a grasping experimentcomparing how different grippers conform around objects.The objects were randomly placed within the grasping rangeof the grippers and hands. Stable grasps were achieved andthe experiments were executed for a total of ten trials. InTable I, we present the results of the grasping benchmarkingfor various adaptive robot grippers and hands, in order toevaluate their grasping capabilities and compare them. Thesponge based parallel jaw gripper and the T42 gripper of theYale OpenHand project [10], were included in this study forcomparison purposes, with T42 being a traditional adaptiverobot gripper and the sponge-based parallel jaw gripper as anexample of extreme compliance. As demonstrated in TableI, the sponge-base gripper failed to provide stable graspsfor objects that are heavy and for objects that have smallcontact areas. So extreme compliance is not beneficial. Thebest gripper assessed in terms of grasp stability was theMSPSA gripper that achieved an 100% success rate andthe second best results were achieved by the T42 and theHA robot hands that couldn’t grasp only the credit card.In Fig. 6, we demonstrate how PSA grippers adapt to non-spherical objects. Although the initial shapes of the fingersare optimized for grasping round objects, the PSA fingersare able to conform to the dice geometry. Similarly, the MS-PSA gripper can adapt to various object geometries and theadditional skin layer provides extra stability for the graspedobjects.

B. Measuring the Contact AreasThe contact surface area of the grippers was measured

using chalk and acrylic paint residues on a layer of paperthat was wrapped around the selected objects. The small cupand mustard bottle were chosen over the other objects due totheir size, that fits within all grippers. Objects were placed inthe same position and covered with appropriate sized blackpaper. Acrylic paint was applied to the fingers surface. Upon

Fig. 5. Grasping capabilities comparison of: a) parallel jaw gripper withHyper-Adaptive fingers (Parallel jaw HA), b) a parallel jaw gripper withMulti-Segmented core Pre-Shaped Adaptive (MS-PSA) fingers, c) a Hyper-Adaptive hand (HA) with fingers based on flexure and spring loaded pinjoints, d) a parallel jaw gripper with sponge-like, compliant fingerpads, ande) the model T42 of the Yale OpenHand project [10]. The objects used are:a small ball, a wooden cube, a mustard bottle, a marble, a small cup, anda jello box. All objects are included in the YCB object set [26]. Subfiguresd) and e) (enclosed in a black frame) focus on grippers that are used forcomparison purposes.

grasping the paint is transferred from the fingers surfacesonto the paper highlighting the respective contact surfaceareas. The painted areas of the paper are then measured.Results are reported in Table II.

Fig. 6. A robot gripper equipped with two Pre-Shaped Adaptive (PSA)robot fingers performing reaching, contacting, and grasping tasks witha dice. Upon contact, the PSA fingers adapts to the object geometry,maximizing the area of the contact patches between the hand and the objectsurface.

Fig. 7. Identification and comparison of contact areas for different types ofhands and grippers grasping two different objects: a small cup (left) and abottle of mustard (right). Green acrylic paint was applied to the finger-padsof the examined robot grippers and hands while yellow chalk was appliedonto the sponge and T42 gripper finger-pads (maintains better contact). Thered boxes enclose the surface areas of the contact patches during grasping.

Results on surface contact area show that for graspingthe mustard container, the sponge-based gripper has thelargest surface contact area, followed by the HA gripper, T42,parallel jaw HA, and MS-PSA. While grasping the smallercup, the HA gripper has the largest contact area followed bythe parallel-jaw HA gripper, the parallel-jaw sponge gripper,the MS-PSA gripper, and T42. From Fig. 7, it is evidentthat for the parallel-jaw HA and HA grippers, a square areaestimate was used. The actual contact area is smaller thanthe estimated area due to gaps between the pin pads.

C. Force Exertion Capabilities

The maximum clench force was also measured for eachgripper. A BioPac SSLA25 dynamometer was placed withinthe grasping workspace of each gripper and the device wasactuated until motor stall. The maximum clench force wasrecorded for each gripper. The parallel jaw gripper had a

Fig. 8. Subfigure (a) presents a dexterous, in-hand manipulation experimentconducted with a CAM hand equipped with one translation module andone rotation module. The gripper uses the concept of extrinsic dexterityto rotate a bottle of Windex spray using the table surface and the rotationmodule of the right finger’s distal phalanx. This is a classic example ofhow the exploitation of certain environmental constraints may facilitate theexecution of manipulation tasks [27]. Subfigure (b) presents a dexterous, in-hand manipulation experiment conducted with a CAM hand equipped withone translation and one rotation module. The robot hand uses the translationmodule of the distal phalanx of the left finger and the proximal phalanx ofthe right finger to unscrew the lid of a jar bottle.

TABLE IICOMPARISON OF DIFFERENT GRIPPERS AND HANDS IN TERMS OF

ACHIEVABLE CONTACT SURFACE AREA AND CLENCH FORCE.

Gripper Contact surface Max clench forceSmall cup Mustard At base

Parallel jaw MS-PSA 1971 mm² 2295 mm² 31 NParallel jaw HA 2754 mm² 3267 mm² 30 N

Parallel jaw Sponge 2250 mm² 4260 mm² 28 NHA 3186 mm² 3645 mm² 9 NT42 896 mm² 3360 mm² 12 N

single Dynamixel high torque XM-430 smart motor whilethe T42, HA and the rotary fingertip module grippers utilizetwo of these motors. Results are reported again in Table II.

The parallel-jaw grippers deliver a much higher grippingforce than the other adaptive grippers. Due to the tendonrouting of the adaptive robot grippers and hands, grippingforce is limited by cable friction and gripper geometry. FromTable II, it is evident that the parallel-jaw sponge-basedgripper had the smallest gripping force. Overall, the parallel-jaw grippers were capable of exerting between 28 N and 31N with each finger.

D. Dexterous, In-Hand Manipulation

In Fig. 8 we present grasping and manipulation experi-ments that demonstrate the efficiency of the CAM hand. TheCAM hand has two fingers and an extra DoF per fingertip.The extra manipulation DoF for the left finger implements alocal translation of the contact, while the extra manipulationDoF for the right finger implements a local rotation of thecontact. Upon contact with the object surface, the extraDoFs start moving. Although the compliance adjustablegripper was characterized by a significant post-contact re-

configuration of the extra DoFs, the grasped object remainsconstrained and the grasping task is executed successfully.More precisely, in Fig. 8 a) a rotation module is used torotate a bottle of Windex spray using the concept of extrinsicdexterity [27]. In Fig. 8 b), a translation module is used tounscrew the lid of a jar. In all cases, upon contact with theobject surface, the load exerted on the finger motors becomesan equivalent displacement of the extra DoF, executing thedesired manipulation task.

E. Video

The accompanying video presents a comprehensive set ofgrasping and manipulation tasks executed with robot handsbased on the proposed designs and concepts. During theexperiments, a wide range of everyday life objects was used.

www.newdexterity.org/structuralcompliance

VI. CONCLUSION

In this paper, we introduced, analyzed, and experimentallyvalidated robot hand paradigms that are based on uncon-ventional uses of structural compliance. These hands canfacilitate and even simplify the execution of dexterous tasks(e.g., grasping or dexterous, in-hand manipulation tasks),without requiring sophisticated sensing elements or com-plicated control laws. More specifically, we proposed pre-shaped, compliant robot fingers that can adapt to differentobject geometries, extracting robust grasps. Subsequently,we presented a design of hyper-adaptive finger pad thatfacilitates the maximization of the area of the contact patchesbetween the robot finger and the grasped object, maximizingalso the stability of the grasps. Finally, we introduced theconcept of the compliance adjustable manipulation by in-troducing compliant elements in-series with the robot hand’stendon routing system. The concept enhances under-actuatedmechanisms by appropriately selecting the imposed tendonloads and taking advantage of the adaptive behavior of thesystem. The efficiency of the proposed concepts and designswas experimentally validated with a variety of experimentalparadigms involving the execution of robust grasping anddexterous, in-hand manipulation tasks with both model andeveryday life objects.

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