Planar, bimanual, whole-arm grasping

Seo, Jung-Won; Kim, Soonkyum; Kumar, Vijay

doi:10.1109/icra.2012.6225086

Cited by 18 publications

(17 citation statements)

References 19 publications

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“…Despite relaxing some of the assumptions, 16,17 analytical methods are still mainly validated in simulations 18,19 or consider 2D objects. [19][20][21] In the last decade, the availability of grasp planning simulators, like GraspIt!, 22 made datadriven methods become popular. These approaches rely on sampling grasp candidates from some knowledge base and rank them according to a specific metric.…”

Section: Introductionmentioning

confidence: 99%

Stable pinching by controlling finger relative orientation of robotic fingers with rolling soft tips

et al. 2017

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SUMMARYThere is a large gap between reality and grasp models that are currently available because of the static analysis that characterizes these approaches. This work attempts to fill this need by proposing a control law that, starting from an initial contact state which does not necessarily correspond to an equilibrium, achieves dynamically a stable grasp and a relative finger orientation in the case of pinching an object with arbitrary shape via rolling soft fingertips. Controlling relative finger orientation may improve grasping force manipulability and allow the appropriate shaping of the composite object consisted of the distal links and the object, for facilitating subsequent tasks. The proposed controller utilizes only finger proprioceptive measurements and is not based on the system model. Simulation and experimental results demonstrate the performance of the proposed controller with objects of different shapes.

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Section: Introductionmentioning

confidence: 99%

Stable pinching by controlling finger relative orientation of robotic fingers with rolling soft tips

et al. 2017

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“…In [4], we showed that every polygon can be immobilized with two planar generalized contacts. Now we present the extension to spatial grasping using spatial generalized contacts introduced in Definition 1.…”

Section: B Immobilization With Generalized Contactsmentioning

confidence: 99%

“…More specifically, we will see that three generalized contacts (an abstraction of the contact interaction between the robot and the object) are needed to obtain immobilizing grasps, whereas only two were required for planar grasping [4]. Thus, initially the configuration is composed of three contact regions, and later additional, available degree-offreedom of an open chain gripper can be exploited to further restrain the object by adding more contacts.…”

Section: Introductionmentioning

confidence: 97%

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Spatial, bimanual, whole-arm grasping

Seo

Kumar

2012

2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

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We address the problem of synthesizing spatial, bimanual, whole-arm grasps by developing the abstractions of an open chain gripper, an open, spatial chain of rigid links and joints between the links, contacting a polyhedral object, and a generalized contact. We show that every general polyhedron can be immobilized by three generalized contacts. We leverage previous work on immobilization to construct an algorithm that synthesizes contact configurations for stable grasping. Our methodology can be applied to grasp a wide range of objects without relying on special-purpose end-effectors as shown in simulations and experiments with a PR2 humanoid robot.

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“…The grasping process depends on many factors, e.g., the physical properties of the object, its functionality, the scene context, the embodiment of the robot and the available sensory information. To cope with the underlying complexity of the problem, many approaches thus apply some form heuristic directly in the state space [29], [32], [26], [18], [6], [II], [20], [13], [14], [23].…”

Section: Background and Related Workmentioning

confidence: 99%

Grasping objects with holes: A topological approach

Pokorny

Stork

Kragić

2013

2013 IEEE International Conference on Robotics and Automation

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Ahstract-This work proposes a topologically inspired ap proach for generating robot grasps on objects with 'holes'.Starting from a noisy point-cloud, we generate a simplicial representation of an object of interest and use a recently devel oped method for approximating shortest homology generators to identify graspable loops. To control the movement of the robot hand, a topologically motivated coordinate system is used in order to wrap the hand around such loops. Finally, another concept from topology -namely the Gauss linking integral -is adapted to serve as evidence for secure caging grasps after a grasp has been executed. We evaluate our approach in simulation on a Barrett hand using several target objects of different sizes and shapes and present an initial experiment with real sensor data.

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Planar, bimanual, whole-arm grasping

Cited by 18 publications

References 19 publications

Stable pinching by controlling finger relative orientation of robotic fingers with rolling soft tips

Stable pinching by controlling finger relative orientation of robotic fingers with rolling soft tips

Spatial, bimanual, whole-arm grasping

Grasping objects with holes: A topological approach

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