Towards performing everyday manipulation activities

Robotics and Autonomous Systems

Volumn 58, Issue 9, 2010, Pages 1085-1095

  Beetz, Michael ^a   Jain, Dominik ^a   Msenlechner, Lorenz ^a   Tenorth, Moritz ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Knowledge processing; Reactive control; Statistical relational learning; Transformational planning

Indexed keywords

CONTROL ARCHITECTURE; FIRST-ORDER; JOB DESCRIPTION; JOB SPECIFICATIONS; KNOWLEDGE PROCESSING; LIVING ENVIRONMENT; MANIPULATION TASK; PERSONAL ROBOT; PROBABILISTIC REASONING; PROOF OF CONCEPT; REACTIVE BEHAVIOR; REACTIVE CONTROL; ROBOT CONTROL SYSTEMS; ROBOT PLAN; STATISTICAL RELATIONAL LEARNING;

ARTIFICIAL INTELLIGENCE; EMPLOYMENT; INTELLIGENT ROBOTS; JOB ANALYSIS; WORLD WIDE WEB;

ROBOT PROGRAMMING;

EID: 77955423304     PISSN: 09218890     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.robot.2010.05.007     Document Type: Article

References (24)

1. Maria Fox, and Derek Long Modelling mixed discrete-continuous domains for planning Journal of Artificial Intelligence Research 27 2006 235 297 (Pubitemid 44681378)
2. Michael Beetz Plan-based Control of Robotic Agents Lecture Notes in Artificial Intelligence vol. LNAI 2554 2002 Springer Publishers
3. Armin Mller, Alexandra Kirsch, Michael Beetz, Transformational planning for everyday activity, in: 17th International Conference on Automated Planning and Scheduling, ICAPS'07, 2007, pp. 248255.
4. Michael Beetz Generality and legibility in mobile manipulation Autonomous Robots Journal (Special Issue on Mobile Manipulation) 28 1 2010 21 44
5. Michael Beetz Structured reactive controllers Journal of Autonomous Agents and Multi-Agent Systems. Special Issue: Best Papers of the International Conference on Autonomous Agents'99 4 March/June 2001 25 55 (Pubitemid 33634322)
6. Michael Beetz Concurrent Reactive Plans: Anticipating and Forestalling Execution Failures Lecture Notes in Artificial Intelligence vol. LNAI 1772 2000 Springer Publishers
7. M. Beetz, and D. McDermott Declarative goals in reactive plans J. Hendler, First International Conference on AI Planning Systems 1992 Morgan Kaufmann 3 12
8. Dominik Jain, Lorenz Msenlechner, Michael Beetz, Equipping robot control programs with first-order probabilistic reasoning capabilities, in: International Conference on Robotics and Automation, ICRA, 2009.
9. C. Matuszek, J. Cabral, M. Witbrock, J. DeOliveira, An introduction to the syntax and content of Cyc, in: 2006 AAAI Spring Symposium, 2006, pp. 4449.
10. C. Fellbaum WordNet: An Electronic Lexical Database 1998 MIT Press USA
11. Radu Bogdan Rusu, Zoltan Csaba Marton, Nico Blodow, Mihai Dolha, and Michael Beetz Towards 3D point cloud based object maps for household environments Robotics and Autonomous Systems Journal 2008
12. Ulrich Klank, Muhammad Zeeshan Zia, Michael Beetz, 3D model selection from an internet database for robotic vision, in: International Conference on Robotics and Automation, ICRA, 2009.
13. Jan Bandouch, Florian Engstler, Michael Beetz, Accurate human motion capture using an ergonomics-based anthropometric human model, in: Fifth International Conference on Articulated Motion and Deformable Objects, AMDO, 2008.
14. Moritz Tenorth, Michael Beetz, KnowRob knowledge processing for autonomous personal robots, in: IEEE/RSJ International Conference on Intelligent RObots and Systems, 2009.
15. M. Tenorth, D. Nyga, M. Beetz, Understanding and executing instructions for everyday manipulation tasks from the world wide web, in: IEEE International Conference on Robotics and Automation, ICRA, 2010.
16. D. McDermott, A reactive plan language. Research Report YALEU/DCS/RR-864, Yale University, 1991.
17. Lorenz Msenlechner, Michael Beetz, Using physics- and sensor-based simulation for high-fidelity temporal projection of realistic robot behavior, in: 19th International Conference on Automated Planning and Scheduling, ICAPS'09, 2009.
18. Lise Getoor, and Ben Taskar Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning) 2007 The MIT Press
19. Matthew Richardson, and Pedro Domingos Markov Logic Networks Machine Learning 62 12 2006 107 136
20. Dominik Jain, Bernhard Kirchlechner, Michael Beetz, Extending Markov logic to model probability distributions in relational domains, in: 30th German Conference on Artificial Intelligence, KI-2007, 2007, pp. 129143.
21. Dominik Jain, Stefan Waldherr, Michael Beetz, Bayesian logic networks, Technical Report, IAS Group, Fakultt fr Informatik, Technische Universitt München, 2009.
22. Robert Mateescu, and Rina Dechter Mixed deterministic and probabilistic networks Annals of Mathematics and Artificial Intelligence 2008
23. Vibhav Gogate, Rina Dechter, SampleSearch: a scheme that searches for consistent samples, in: AISTATS, 2007.
24. Hoifung Poon, and Pedro Domingos Sound and efficient inference with probabilistic and deterministic dependencies AAAI 2006 AAAI Press