An Approach for Modeling Grasping Configuration Using Ontology-based Taxonomy

Abstract

The handling of flexible materials is complicated task in robotics and automation. Due to deformability and fragility of flexible materials, robots are equipped with the state-of-the-art sensors and grippers to perform such tasks. Nonetheless, industry still lacks for approaches and techniques for handling these materials. Therefore, several industries and mass production systems require hiring human to perform the deformable materials-related task. These tasks might include usage of toxic martials (e.g. carbon fiber sheets) or dangerous tools (e.g. sharp cutting knives). In this regard, this paper presents an approach for selecting grasping configuration of objects based on the product's properties such as rigidity, surface roughness and shape, and the required task. Briefly, this research is based on several published taxonomies for modeling the hand of the human while grasping different objects. After refining the taxonomy, an ontology model is populated which will be queried for specifying the gripper's properties such as number of fingers and required grasping force that can perform the selected task on the selected product. Finally, this research presented a use case form the REMODEL (Robotic tEchnologies for the Manipulation of cOmplex DeformablE Linear objects) project in order to assess and validate the approach. For the future, this research expected to include the selection of the grippers, the robotic arm and its approach for grasping the product.