Polygonizations of point sets in the plane
Discrete & Computational Geometry
The quickhull algorithm for convex hulls
ACM Transactions on Mathematical Software (TOMS)
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
ACM Transactions on Graphics (TOG)
High-Dimensional Similarity Joins
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Shape-Similarity Search of Three-Dimensional Models Using Parameterized Statistics
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
A Geometric Approach to 3D Object Comparison
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Heuristic approach for multiple queries of 3D N-finger frictional force closure grasp
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Regrasp planning in the grasp space using independent regions
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
On the Passive Force Closure Set of Planar Grasps and Fixtures
International Journal of Robotics Research
International Journal of Robotics Research
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This paper addresses the problem of defining a simple End-Effector design for a robotic arm that is able to grasp a given set of planar objects. The OCOG (Objects COmmon Grasp search) algorithm proposed in this paper searches for a common grasp over the set of objects mapping all possible grasps for each object that satisfy force closure and quality criteria by taking into account the external wrenches (forces and torque) applied to the object. The mapped grasps are represented by feature vectors in a high-dimensional space. This feature vector describes the design of the gripper. A database is generated for all possible grasps for each object in the feature vector space. A search algorithm is then used for intersecting all possible grasps over all parts and finding a common grasp suitable for all objects. The search algorithm utilizes the kd-tree index structure for representing the database of the sets of feature vectors. The kd-tree structure enables an efficient and low cost nearest-neighbor search for common vectors between the sets. Each common vector found (feature vector) is the grasp configuration for a group of objects, which implies the future end-effector design. The final step classifies the grasps found to subsets of the objects, according to the common vectors found. Simulations and experiments are presented for four objects to validate the feasibility of the proposed algorithm. The algorithm will be useful for standardization of end-effector design and reducing its engineering time.