Hybrid Roller-Jamming Gripper for Object Acquisition and Retention Under Pose Uncertainty

Yijie Ren; Guillaume Gourmelen; Hiroyasu Iwata

cs.ROAug 21, 2026

Hybrid Roller-Jamming Gripper for Object Acquisition and Retention Under Pose Uncertainty

Authors: Yijie Ren, Guillaume Gourmelen, Hiroyasu Iwata

Organizations: Department of Modern Mechanical Engineering, Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan

Abstract

In household manipulation, pose uncertainty often results in off-centre or partial initial contact, making reliable object acquisition difficult. Roller-based grippers can actively draw objects inward but often provide limited post-capture stability, whereas granular-jamming grippers require sufficient contact before jamming to achieve strong retention. This paper presents a hybrid roller-jamming gripper that integrates active object intake and post-capture retention within a single gripper. The proposed gripper uses inward roller rotation to increase contact and draw the object toward the gripper centre, followed by vacuum-induced granular jamming to stiffen the rollers and stabilise the grasp. The paper also presents a simplified geometric analysis of the gripper and a bench-level characterisation of the prototype's force capability. The gripper prototype was mounted on a 7-DoF robotic arm and evaluated using eight test objects. Furthermore, controlled planar position and orientation offsets were applied, with each condition repeated three times. The main evaluation comprised 840 grasp trials, including 216 planar-offset trials and 624 orientation-offset trials. Overall, the gripper succeeded in 812/840 trials: 215/216 planar-offset trials and 597/624 orientation-offset trials. The ablation evaluation comprised 162 trials on three objects. The roller-only and jamming-only conditions achieved 54/81 and 24/81 successes, respectively, showing their different contributions. These results provide initial mechanism-level evidence that hybrid roller-jamming is a promising strategy for improving acquisition and retention after imperfect first contact.

Figures & tables

System	Primary purpose	Acquisition mechanism	Retention mechanism	Actuation architecture
RBO Hand 2 [ 3 ]	Dexterous grasping through compliance and underactuation	Pneumatic bending of compliant fingers and palm around the object	Compliant enveloping contact maintained by pneumatic pressure	Seven pneumatic actuators grouped into four control channels
Two-fingered hand with jamming finger tips [ 10 ]	Adaptive grasping with variable-stiffness fingertips	Finger closure with passive fingertip conformity	Vacuum-jammed fingertips	Four servomotors and a pneumatic jamming system
Simple Belted Parallel-Jaw Gripper [ 16 ]	Grasp-to-grasp in-hand translation and reorientation	Base parallel-jaw closure	Force-controlled jaw clamping with belt and finger-surface contact	Four independent belt motors plus the base-gripper actuator
Roller Grasper V3 [ 19 ]	Full 6-DoF in-hand manipulation	Finger closure followed by rolling pickup	Four-finger rolling contact, assisted by an active palm	Four fingers with three active DoF each; 12 active DoF
Mecanum-wheel hand [ 20 ]	Omnidirectional in-hand manipulation without finger gaiting	Coupled four-finger opening and closing	Force closure with spring-loaded wheel constraint forces	Three-servo coupled reconfiguration and two wheel-drive motors
Proposed roller-jamming gripper	Grasp acquisition and retention under pose offsets	Shared finger closure followed by inward rolling intake	Vacuum-induced granular jamming of the same rollers	Three active DoF and pneumatic vacuum switching

TABLE I: Comparison with representative compliant, jamming-based, and active-surface grippers. The systems address different tasks and are compared primarily by their mechanisms and actuation requirements.

Fig. 1: Prototype of the proposed roller-jamming gripper mounted on a 7-DoF robot arm (xArm7).

Fig. 2: Mechanical architecture of the proposed gripper: (Left) overall assembly and (Right) base module, showing the gripper palm, mounting adapter, XM430 actuator, and worm-gear finger-closing transmission.

Fig. 3: Roller-finger architecture: (Left) roller-finger module with the XL320-driven worm-gear transmission and (Right) spherical membrane roller construction, including the clamp rings, drive interface, and rotary union for vacuum feedthrough.

Item	Value
Overall envelope (W $\times$ L $\times$ D)	$70\times 228\times 177\,\mathrm{mm}$
Total gripper mass	$1.31\,\mathrm{kg}$
Spherical membrane roller diameter	$\approx 80\,\mathrm{mm}$
Roller axial width	$73\,\mathrm{mm}$
Finger pivot to roller centre	$115.6\,\mathrm{mm}$
Max roller centre-to-centre distance	$285\,\mathrm{mm}$

TABLE II: Key mechanical specifications of the gripper.

Fig. 4: Membrane mould components: (Left) internal core and alignment shaft and (Right) assembled two-part mould containing the core shell and outer cavity used to form the spherical dimpled membrane.

Fig. 5: Control, communication, electrical-power, and pneumatic architecture of the prototype gripper system.

Fig. 6: Simplified front-view rigid-envelope model of the gripper. The fingers rotate symmetrically about pivots separated by $d_{p}$ , with pivot-to-roller-centre distance $L$ , roller radius $R$ , and roller-centre spacing $d_{c}$ .

Fig. 7: Nominal fully closed geometry used to estimate the minimum supported circular-feature radius $r_{\min}$ . The undeformed roller envelopes have radius $R$ and centre-to-centre spacing $d_{c}(\theta_{\min})$ .

Fig. 8: Simplified front-view tilted-contact geometry used to estimate the minimum supported circular-feature radius. The roller pair is tilted by $\Delta\theta$ while maintaining the nominal centre spacing $d_{c}(\theta_{\min})$ . The supported feature remains tangent to both undeformed roller envelopes and the support plane.

Fig. 9: Preliminary bench force tests. Force time histories from the single roller-traction, grasp slip-out-resistance, and clamping-force trials. The maximum measured forces were 8.4, 25.6, and 27.7 N, respectively.

Fig. 10: Finite-state machine of the grasp controller. CLOSE and HOLD use motor-current and dwell conditions, whereas INTAKE and JAM use prescribed durations. Abort or manual-release commands return the system to RELEASE .

Fig. 11: Experimental setup (top) and example of camera-based object localisation (bottom). For the T-shirt, pressure gauge, and cable, the overhead camera estimates the object centroid on the tabletop and in-plane extents after each manual reset. AprilTags define the tabletop reference frame used for localisation and offset generation.

Fig. 12: Test objects used for evaluation: pen, marble, gallon jug, plastic cup, paper sheet, T-shirt, pressure gauge, and cable

Object	Mass [g]	Physical characteristics	Contact challenge represented
Pen	24.6	Rigid, slender, and low-profile	Shallow contact with a narrow object.
Marble	19.9	Rigid, smooth, small, and spherical	Localised contact and enclosure of a small sphere.
Gallon jug	420	Rigid, large, and relatively heavy	Retention of a large object under higher loading.
Plastic cup	6.0	Lightweight, thin-walled, and deformable	Grasping without excessive deformation.
Paper sheet	4.2	Thin, flat, flexible, and low-profile	Shallow and potentially one-sided contact.
T-shirt	180	Highly deformable textile	Changing shape and contact region during acquisition.

TABLE III: Physical characteristics and contact challenges represented by the test objects.

Object	Planar/ablation grasp height [mm]	Orientation grasp height [mm]	Intake duration [s]	CLOSE current threshold [mA]	HOLD current threshold [mA]
Pen	6	6	5	40	200
Marble	10	10	5	130	230
Gallon jug	254	254	2	80	230
Plastic cup	58	58	4	40	200
Paper sheet	-10	-10	5	70	70
T-shirt	0	6	8	40	200

TABLE IV: Object-specific parameters used in the repeated experiments.

Test protocol	Successful trials	Success rate	95% CI
Planar offset	215/216	99.5%	97.4–99.9%
Orientation offset	597/624	95.7%	93.8–97.0%
Main evaluation	812/840	96.7%	95.2–97.7%
JAM OFF	54/81	66.7%	55.9–76.0%
ROLLER OFF	24/81	29.6%	20.8–40.3%

TABLE V: Success rate across the test protocols with two-sided 95% Wilson score confidence intervals.

Fig. 13: Successful grasps with the roller-jamming gripper on the eight test objects used in evaluation. Top row (left to right): pen, marble, gallon jug, plastic cup. Bottom row (left to right): paper sheet, T-shirt, pressure gauge, cable.

Fig. 14: Planar-offset test results for the eight objects, with three trials per condition. Each coloured marker corresponds to one offset condition repeated three times; the marker colour indicates the number of successful trials out of three. Offsets are applied on a $3\times 3$ grid about the estimated object centre and scaled to $\pm 20\%$ of the corresponding in-plane object extents.

Fig. 15: Ablation results for the pen, gallon jug, and cable under the planar-offset protocol. The top row shows the roller-only condition (JAM OFF), and the bottom row shows the jamming-only condition (ROLLER OFF). Marker colour indicates the number of successful trials out of three at each offset.

Fig. 16: Orientation-offset test results across the roll, pitch, and yaw conditions, with three trials per condition. Each cell represents one orientation-offset condition repeated three times, and the number and colour in each cell indicate the number of successful trials out of three. The $3\times 3\times 3$ roll–pitch–yaw grid excludes the all-zero condition, shown in grey as not tested. For the paper sheet, the orientation-offset magnitude was reduced to $\pm 5^{\circ}$ to avoid gripper–table collision.

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Robots are increasingly used in unstructured environments. The need for them to safely grasp unknown objects without damaging them becomes crucial. Humans achieve this by sensing and quickly responding by adjusting their grasping force. Similarly, effective grasp acquisition in robots requires compliant interaction strategies that can adapt to uncertain object properties and adjust to any instabilities during manipulation. We present a geometry-aware force/torque-based contact estimation method for a coarse position-controlled gripper, combined with an adaptive admittance controller for safe grasp acquisition. The desired contact forces are estimated online to keep stable contact with objects of unknown properties. This enables compliant and stable grasps while avoiding excessive forces. Experiments with objects of different sizes, shapes, stiffnesses, and weights show that the proposed algorithm not only prevents slippage but also applies minimal force to safely grasp an object without causing excessive deformation.

Abstract

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