Structured Design and Development of Domain-Specific Languages in Robotics

Robot programming is an interdisciplinary and knowledge-intensive task. All too often, knowledge of the different robotics domains remains implicit. Although, this is slowly changing with the rising interest in explicit knowledge representations through domain-specific languages (DSL), very little is known about the DSL design and development processes themselves. To this end, we present and discuss the reverse-engineered process from the development of our Grasp Domain Definition Language (GDDL), a declarative DSL for the explicit specification of grasping problems. An important finding is that the process comprises similar building blocks as existing software development processes, like the Unified Process.

[1]  Moritz Tenorth,et al.  KnowRob: A knowledge processing infrastructure for cognition-enabled robots , 2013, Int. J. Robotics Res..

[2]  Gerd Hirzinger,et al.  Grasp planning: how to choose a suitable task wrench space , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[3]  Mp Foster.  Disambiguating the SI notation would guarantee its correct parsing , 2009, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[4]  Shinichi Hirai,et al.  Robust real time material classification algorithm using soft three axis tactile sensor: Evaluation of the algorithm , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[5]  Gerhard K. Kraetzschmar,et al.  Declarative specification of task-based grasping with constraint validation , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  M Mernik,et al.  When and how to develop domain-specific languages , 2005, CSUR.

[7]  Douglas C. Schmidt,et al.  Guest Editor's Introduction: Model-Driven Engineering , 2006, Computer.

[8]  Darwin G. Caldwell,et al.  Code generation of algebraic quantities for robot controllers , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Mark R. Cutkosky,et al.  On grasp choice, grasp models, and the design of hands for manufacturing tasks , 1989, IEEE Trans. Robotics Autom..

[10]  Joris De Schutter,et al.  Geometric Relations Between Rigid Bodies (Part 1): Semantics for Standardization , 2013, IEEE Robotics & Automation Magazine.

[11]  Frank Budinsky,et al.  Eclipse Modeling Framework , 2003 .

[12]  Peter K. Allen,et al.  Graspit! A versatile simulator for robotic grasping , 2004, IEEE Robotics & Automation Magazine.

[13]  Danica Kragic,et al.  Task-Based Grasp Adaptation on a Humanoid Robot , 2012, SyRoCo.

[14]  Joris De Schutter,et al.  Reusable hybrid force-velocity controlled motion specifications with executable Domain Specific Languages , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Dmitry Berenson,et al.  Grasp planning in complex scenes , 2007, 2007 7th IEEE-RAS International Conference on Humanoid Robots.

[16]  Herman Bruyninckx,et al.  The BRICS component model: a model-based development paradigm for complex robotics software systems , 2013, SAC '13.

[17]  P. Krutchen,et al.  The Rational Unified Process: An Introduction , 2000 .

[18]  Joris De Schutter,et al.  Geometric Relations between Rigid Bodies : Semantics for Standardization , 2012 .