@techreport{Schneider2014,
  author    = {Sven Schneider},
  title     = {Design of a declarative language for task-oriented grasping and tool-use with dextrous robotic hands},
  isbn      = {978-3-96043-012-4},
  issn      = {1869-5272},
  doi       = {10.18418/978-3-96043-012-4},
  url       = {https://nbn-resolving.org/urn:nbn:de:hbz:1044-opus-204},
  institution = {Fachbereich Informatik},
  series    = {Technical Report / University of Applied Sciences Bonn-Rhein-Sieg. Department of Computer Science},
  pages     = {XII, 77},
  year      = {2014},
  abstract  = {Apparently simple manipulation tasks for a human such as transportation or tool use are challenging to replicate in an autonomous service robot. Nevertheless, dextrous manipulation is an important aspect for a robot in many daily tasks. While it is possible to manufacture special-purpose hands for one specific task in industrial settings, a generalpurpose service robot in households must have flexible hands which can adapt to many tasks. Intelligently using tools enables the robot to perform tasks more efficiently and even beyond the designed capabilities. In this work a declarative domain-specific language, called Grasp Domain Definition Language (GDDL), is presented that allows the specification of grasp planning problems independently of a specific grasp planner. This design goal resembles the idea of the Planning Domain Definition Language (PDDL). The specification of GDDL requires a detailed analysis of the research in grasping in order to identify best practices in different domains that contribute to a grasp. These domains describe for instance physical as well as semantic properties of objects and hands. Grasping always has a purpose which is captured in the task domain definition. It enables the robot to grasp an object in a taskdependent manner. Suitable representations in these domains have to be identified and formalized for which a domain-driven software engineering approach is applied. This kind of modeling allows the specification of constraints which guide the composition of domain entity specifications. The domain-driven approach fosters reuse of domain concepts while the constraints enable the validation of models already during design time. A proof of concept implementation of GDDL into the GraspIt! grasp planner is developed. Preliminary results of this thesis have been published and presented on the IEEE International Conference on Robotics and Automation (ICRA).},
  language  = {en}
}