Controlling Palm-Object Interactions Via Friction for Enhanced In-Hand Manipulation

Teeple, Clark B.; Aktaş, Buse; Yuen, Michelle C.; Kim, Grace; Howe, Robert D.; Wood, Robert J.

doi:10.1109/lra.2022.3143578

Cited by 8 publications

(7 citation statements)

References 30 publications

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“…Teeple et al [13], [65] presented different types of actuated palms for a continuous soft gripper with four fingers [66]. In [13], a 1-DoF rigid telescoping mechanism which moves along the direction perpendicular to the fingers' bases was introduced [Fig.…”

Section: Table III Table Reporting the Analyzed Actuated Palms For So...mentioning

confidence: 99%

“…The palm actuation allows to change its diameter and height simultaneously and on-the-fly, providing an extra support to objects of different sizes during mid-air in-hand manipulation tasks. In [65], two different palm designs aimed at changing the friction force at the contact between the palm and the object are presented. The first one allows to vary the friction coefficient, whereas the second one allows to vary the preload normal force.…”

Section: Table III Table Reporting the Analyzed Actuated Palms For So...mentioning

confidence: 99%

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Actuated Palms for Soft Robotic Hands: Review and Perspectives

Pozzi,

Malvezzi,

Prattichizzo

et al. 2024

IEEE/ASME Trans. Mechatron.

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Section: Table III Table Reporting the Analyzed Actuated Palms For So...mentioning

confidence: 99%

Section: Table III Table Reporting the Analyzed Actuated Palms For So...mentioning

confidence: 99%

Actuated Palms for Soft Robotic Hands: Review and Perspectives

Pozzi,

Malvezzi,

Prattichizzo

et al. 2024

IEEE/ASME Trans. Mechatron.

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“…Specifically, in-hand manipulation has emerged as an active research domain in recent years. Works such as those cited in [1], [2] have proficiently tackled challenges associated arXiv:2308.16480v1 [cs.RO] 31 Aug 2023 Fig. 2: Pipeline of the small-object grasping, pinching, classifying, and sorting process.…”

Section: Related Workmentioning

confidence: 99%

DenseTact: Optical Tactile Sensor for Dense Shape Reconstruction

Do¹,

Kennedy²

2022

2022 International Conference on Robotics and Automation (ICRA)

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Collaborative robots stand to have an immense impact both on human welfare in domestic service applications and industrial superiority in advanced manufacturing requires dexterous assembly. The outstanding challenge is providing robotic fingertips with a physical design that makes them adept at performing dexterous tasks that require high-resolution, calibrated shape reconstruction and force sensing. In this work, we present DenseTact 2.0, an optical-tactile sensor capable of visualizing the deformed surface of a soft fingertip and using that image in a neural network to perform both calibrated shape reconstruction and 6-axis wrench estimation. We demonstrate the sensor accuracy of 0.3633mm per pixel for shape reconstruction, 0.410N for forces, 0.387mmN •m for torques, and the ability to calibrate new fingers through transfer learning, achieving comparable performance that trained more than four times faster with only 12% of the dataset size.

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“…Despite significant advances in robotic grippers, their performance in dynamic scenarios is still not comparable to biological grippers. For grasping static targets, existing grippers rely on mechanical interlocking 25 , frictional grip 26 , and adhesion grip 17 , 27 , which have enriched the envelope form between graspers and objects. Similarly, researchers using variable stiffness materials or structures 28 , 29 , biomimetic adhesive sheets 17 , 30 , 31 , and variable configuration designs 32 have made grippers compatible with objects of different shapes, masses, scales, and textures.…”

Section: Introductionmentioning

confidence: 99%

“…on mechanical interlocking 25 , frictional grip 26 , and adhesion grip 17,27 , which have enriched the envelope form between graspers and objects. Similarly, researchers using variable stiffness materials or structures 28,29 , biomimetic adhesive sheets 17,30,31 , and variable configuration designs 32 have made grippers compatible with objects of different shapes, masses, scales, and textures.…”

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confidence: 99%

Finger-palm synergistic soft gripper for dynamic capture via energy harvesting and dissipation

Zhang

Gao

et al. 2022

Nat Commun

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Robotic grippers, inspired by human hands, show an extraordinary ability to manipulate objects of various shapes, sizes, or materials. However, capturing objects with varying kinetic energy remains challenging, regardless of the classical rigid-bodied or frontier soft-bodied grippers. Here, we demonstrate a rapid energy harvesting and dissipation mechanism for the soft grippers leveraging the finger-palm synergy. Theoretically and experimentally, this mechanism enables a soft gripper to reliably capture high-speed targets by dissipating and harvesting almost all the target’s kinetic energy within 30 milliseconds. The energy harvesting and dissipating capability are adjustable and can be enhanced by inflating pressure. Additionally, the harvested energy is autonomously transferred into fingers to enhance their grasping force and reduce the response time. To highlight, the grippers we developed are integrated into a six-rotor drone and successfully capture flying objects in an outdoor experiment. These results significantly advance robotics development in achieving dynamic capture of dynamic targets.

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Controlling Palm-Object Interactions Via Friction for Enhanced In-Hand Manipulation

Cited by 8 publications

References 30 publications

Actuated Palms for Soft Robotic Hands: Review and Perspectives

Actuated Palms for Soft Robotic Hands: Review and Perspectives

DenseTact: Optical Tactile Sensor for Dense Shape Reconstruction

Finger-palm synergistic soft gripper for dynamic capture via energy harvesting and dissipation

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