Optimization of grasping by using a required external force set

Watanabe, Tetsuyou; Yoshikawa, Tsuneo

doi:10.1109/robot.2003.1241744

Cited by 30 publications

(33 citation statements)

References 22 publications

(1 reference statement)

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“…This indicates that the normal way of grasping by increasing the pressure on the object does not work well for grasping a sheet. Conventional grasping methods (for example, see [17], [18]) may not work for sheet grasping. In the comparison of the theoretical and experimental results, the theoretical results were close to the experimental results.…”

Section: Comparison Between Theory and Experimental Resultsmentioning

confidence: 99%

“…In sum, various levels of softness for the fingertips have both merits and demerits, and the type of fingertip should be selected according to the task. The conventional metric evaluating grasping (for example, see [17], [18]) evaluates based on convex theory. Therefore, if the magnitude of grasping forces was set to be twice, the magnitude of resistible force also got to be twice, irrespective of stiffness of fingertips.…”

Section: B Results and Discussionmentioning

confidence: 99%

“…The balancing of a large external force is one metric for evaluating the grasping stability (e.g., see [17], [18]). In our situation of sheet grasping, the external force in the direction of the gravitational force is critical, as the effect of gravity is maximum in this direction.…”

Section: Grasping Stability Analysismentioning

confidence: 99%

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Bent Sheet Grasping Stability for Sheet Manipulation

Fujihira

Nishimura

Watanabe

2016

IEEE Robot. Autom. Lett.

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Abstract-In this study, we focused on sheet manipulation with robotic hands. This manipulation involves grasping the sides of the sheet and utilizing the convex area resulting from bending the sheet. This sheet manipulation requires the development of a model of a bent sheet grasped with fingertips. We investigated the relationship between the grasping force and bending of the sheet and developed a bent sheet model. We also performed experiments on the sheet grasping stability with a focus on the resistible force, which is defined as the maximum external force at which a fingertip can maintain contact when applying an external force. The main findings and contributions are as follows: 1) After the sheet buckles, the grasping force only increases slightly even if the fingertip pressure is increased.2) The range of the applicable grasping forces depends on the stiffness of the fingertips. Stiffer fingertips cannot provide a small grasping force but can resist large external forces. Softer fingertips can provide a small grasping force but cannot resist large external forces. 3) A grasping strategy for sheet manipulation is presented that is based on controlling the stiffness of the fingertips.

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Section: Comparison Between Theory and Experimental Resultsmentioning

confidence: 99%

Section: B Results and Discussionmentioning

confidence: 99%

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Bent Sheet Grasping Stability for Sheet Manipulation

Fujihira

Nishimura

Watanabe

2016

IEEE Robot. Autom. Lett.

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“…Finding an optimal grasp is e.g. reported by Watanabe et al [108]. Mishra [78] shows that in a planar case an optimal three finger grasp can can be computed efficiently.…”

Section: Grasp Planningmentioning

confidence: 99%

Knowledge Representations for Planning Manipulation Tasks

Zacharias

2012

Cognitive Systems Monographs

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A complex manipulation task for a robot has to be planned on different levels of abstraction before it can be executed on a real system. At a high-level of abstraction, a task planner generates a sequence of subtasks from a given abstract command, its pre-and postconditions and a current world model. To restrict the already huge search space of the task planner, aspects like geometric information are not contained in the world model at this level. The task planner then assigns the subtasks to planners on a lower level of abstraction like path planners or grasp planners. These planners rely on geometric information to compute their solutions. However, without considering geometric information the task planner cannot determine good parameters for these low-level planners. Therefore, the derived plans may not be valid for a given situation and may require backtracking. Knowledge representations can bridge the gap between these planning levels and thereby enable scene reasoning. The kinematic capabilities of a robot are one aspect the task planner has to be aware of. Therefore this thesis introduces a novel general representation of the kinematic capabilities of a robot arm. The versatile workspace is defined to describe in which orientations the end effector attached to a robot arm can reach a position. The capability map is a calculable representation of the versatile workspace that allows to determine how well regions of the workspace are reachable. It accurately represents the versatile workspace of arbitrary arm kinematics and enables autonomous taskspecific reasoning. Furthermore, its visualization scheme is intuitively comprehensible for the human. The versatile applicability of the capability map is shown by examples from several distinct application domains. In human-robot interaction, the capability map is used to objectively evaluate a bi-manual interface for tele-operation. The results can also supplement the design process for humanoid robot design. In low-level geometric planning, the capability map is used to reduce the search space and to parameterize path planners and grasp planners. Thus, in a manipulation task for a humanoid robot more human-like motion is planned while simultaneously the computation time is reduced. In high-level task reasoning, the capability map is used to evaluate how well a robot is suited for a task. In an example a humanoid robot has to perform a task involving 3D trajectories. Regions are extracted from the capability map that permit the task execution and the suitability of the robot is inferred.

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“…Garg and Dutta [28] shown that the internal forces required for grasping deformable objects vary with size of object and finger contact angle. In [29], Watanabe and Yoshikawa investigated optimal contact points on an arbitrary shaped object in 3D using the concept of required external force set. Ding et al proposed an algorithm for computing form closure grasp on a 3D polyhedral object using local search strategy in [30].…”

Section: Issues and Prior Researchmentioning

confidence: 99%