TY - GEN

T1 - A common 3-finger grasp search algorithm for a set of planar objects

AU - Sintov, Avishai

AU - Raghothama, Srinivas

AU - Menassa, Roland

AU - Shapiro, Amir

PY - 2012

Y1 - 2012

N2 - This work proposes an algorithm for designing a simple End Effector configuration for a robotic arm which is able to grasp a given set of objects. The algorithm searches for a common 3-finger grasp over a set of objects. The search algorithm maps all possible grasps for each object which satisfy a quality criterion and takes into account an external wrench (force and torque) applied to the object. The mapped grasps are represented by feature vectors in a high-dimensional space. This feature vector describes the shape of the gripper. We then generate a database of all possible grasps for each object represented as points in the feature vector space. Then we use another search algorithm for intersecting all points over the entire sets and finding common points suitable for all objects. Each point (feature vector) is the grasp configuration for a group of objects, which implies for the end-effector design. The final step classifies the grasps found to subsets of the objects, according to the common points found, this with preference to find one grasp to all the objects. The algorithm will be useful for assembly line robots in reducing end-effector design time, end-effector manufacturing time and final product cost.

AB - This work proposes an algorithm for designing a simple End Effector configuration for a robotic arm which is able to grasp a given set of objects. The algorithm searches for a common 3-finger grasp over a set of objects. The search algorithm maps all possible grasps for each object which satisfy a quality criterion and takes into account an external wrench (force and torque) applied to the object. The mapped grasps are represented by feature vectors in a high-dimensional space. This feature vector describes the shape of the gripper. We then generate a database of all possible grasps for each object represented as points in the feature vector space. Then we use another search algorithm for intersecting all points over the entire sets and finding common points suitable for all objects. Each point (feature vector) is the grasp configuration for a group of objects, which implies for the end-effector design. The final step classifies the grasps found to subsets of the objects, according to the common points found, this with preference to find one grasp to all the objects. The algorithm will be useful for assembly line robots in reducing end-effector design time, end-effector manufacturing time and final product cost.

UR - http://www.scopus.com/inward/record.url?scp=84872515336&partnerID=8YFLogxK

U2 - 10.1109/CoASE.2012.6386331

DO - 10.1109/CoASE.2012.6386331

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AN - SCOPUS:84872515336

SN - 9781467304283

T3 - IEEE International Conference on Automation Science and Engineering

SP - 1095

EP - 1100

BT - 2012 IEEE International Conference on Automation Science and Engineering

T2 - 2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012

Y2 - 20 August 2012 through 24 August 2012

ER -