Grasp planning methodology for 3d arbitrary shaped objects
- Autores: Máximo Alejandro Roa Garzón
- Directores de la Tesis: Raúl Suárez Feijóo (dir. tes.)
- Lectura: En la Universitat Politècnica de Catalunya (UPC) ( España ) en 2009
- Idioma: español
- Tribunal Calificador de la Tesis: Luis Basañez Villaluenga (presid.), Joan Rosell Gratacos (secret.), Claudio Melchiorri (voc.), Antonio Morales Escrig (voc.), Rafael Aracil Santonja (voc.)
- Materias:
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- Resumen
Object grasping and manipulation has become an area of great interest in robotics, specially due to the development of dexterous grasping devices like anthropomorphic hands that increase the flexibility and versatility of the robot arms, allowing the grasping and manipulation of a large variety of objects with a single end effector. This thesis tackles several planning problems associated with grasping and manipulation of arbitrary discrete objects, i.e. objects described with a cloud of points or a polygonal mesh.
The computation of a force closure grasp and a locally optimal grasp is tackled using oriented search procedures based on geometric reasoning in the wrench space. The grasp quality measure considered is the largest perturbation wrench that the grasp can resist independently of the perturbation direction. However, real mechanical hands and grasping devices can hardly assure that the fingers will precisely touch the object at the computed contact points. Independent contact regions (ICRs) such that a finger contact in each ICR ensures a force closure grasp, provide robustness in front of finger positioning errors. This thesis presents an approach to compute ICRs with any number of frictionless or frictional contacts on the surface of any 3D object, assuring a controlled minimum grasp quality. The approach generates the ICRs by growing them around the contact points of a given appropriated starting grasp, like for instance a locally optimal grasp. The approach is also extended to compute the ICRs when several contacts are fixed beforehand.
The notion of Non-Graspable Regions (NGRs) is introduced in this work, such that a finger contact in each NGR always produces a non-force closure grasp independently of the exact position of each finger. The ICRs and NGRs are used to efficiently explore the grasp space. The grasp space is constructed using a sampling method that provides samples of force closure or non force closure grasps used to compute ICRs or NGRs, respectively, which are used to label the configurations of the grasp space. An efficient deterministic sampling sequence is provided to allow a good incremental and uniform exploration of the grasp space. The generation of the grasp space is then applied to solve the regrasping problem, i.e. to obtain trajectories of the fingertips on the object surface in order to change from an initial to a final grasp without losing the force closure condition.
Application examples are included to illustrate the relevance and performance of the proposed approaches.
