D.Ing. / The grasping strategy for a three dimensional object by a robotic gripper requires a geometrical reasoning and analysis of the physical gripper design, control and operation. The work addresses the problem of data acquisition and processing required for an object recognition and its application in the selection of grasping strategy for a given gripper. The system described in the thesis integrates the analyses of image data, object geometry and grasping operation in a systematic way. It is hierarchically constructed in several levels of analyses and processes including object recognition, grasping feature representation and classification, matching strategy for objects and the gripper and grasping description and operation. Object shape features are taken for recognition based on the image data collected through an infrared sensor. With a face relation graph proposed, an object model is built for describing the object geometrical properties and extracting its grasping features. A coding system based on group technology concepts is proposed for object classification. It describes object features relative to grasping operation. Gripping models are established and incorporated with the coding system for analysis of object gripping features. By means of the gripping models and the coding system, objects to be grasped are classified and grouped into specific families according to their similarities in gripping. The information transformation between the object and the gripper is made through a matrix representation. An object matrix describes the selection of gripping faces and object geometry for gripping , while a gripper matrix describes the fingers selection and its configuration in correspondence with the object to be grasped. The matching of the matrices is established through a knowledge-based reasoning approach. The grasping operation is controlled by a computer in terms of the commands generated by the gripper matrix through a gripper code. The design of the generic gripper for this application is described.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:10115 |
Date | 12 September 2012 |
Creators | Huang, Jianan |
Source Sets | South African National ETD Portal |
Detected Language | English |
Type | Thesis |
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