TAPIR: A software Toolkit for approximating and adapting POMDP solutions online

Australasian Conference on Robotics and Automation, ACRA

Volumn 02-04-December-2014, Issue , 2014, Pages

  Klimenko, Dimitri ^a   Song, Joshua ^a   Kurniawati, Hanna ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SOFTWARE; MACHINE DESIGN; MARKOV PROCESSES; TREES (MATHEMATICS);

CONTROL ERRORS; HIGH-FIDELITY SIMULATORS; MODULAR DESIGNS; MOTION STRATEGY; PARTIALLY OBSERVABLE MARKOV DECISION PROCESS; SENSOR RELIABILITIES; SOFTWARE TOOLKITS; USER FRIENDLINESS;

ROBOTICS;

EID: 84994711783     PISSN: 14482053     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. [Bai et al., 2010] H. Bai, D. Hsu, W. S. Lee, and A. V. Ngo. Monte Carlo value iteration for continuous-state POMDPs. In WAFR, 2010.
2. [Bai et al., 2012] H. Bai, D. Hsu, M. J. Kochenderfer, and W. S. Lee. Unmanned aircraft collision avoidance using continuousstate POMDPs. In RSS, 2012.
3. [E. Rohmer, 2013] M. Freese E. Rohmer, S. P. N. Singh. V-REP: a versatile and scalable robot simulation framework. In IROS, 2013.
4. [Hauser, 2010] K. Hauser. Randomized belief-space replanning in partially-observable continuous spaces. In WAFR, 2010.
5. [He et al., 2010] R. He, E. Brunskill, and N. Roy. PUMA: planning under uncertainty with macro-actions. In AAAI, 2010.
6. [Hornung et al., 2013] Armin Hornung, Kai M. Wurm, Maren Bennewitz, Cyrill Stachniss, and Wolfram Burgard. OctoMap: An efficient probabilistic 3D mapping framework based on octrees. Autonomous Robots, 2013. Software available at http://octomap. github.com.
7. [Horowitz and Burdick, 2013] M. Horowitz and J. Burdick. Interactive non-prehensile manipulation for grasping via POMDPs. In ICRA, 2013.
8. [Kaelbling et al., 1998] L. Kaelbling, M. Littman, and A. Cassandra. Planning and acting in partially observable stochastic domains. AI, 101:99-134, 1998.
9. [Kocsis and Szepesvri, 2006] L. Kocsis and C. Szepesvri. Bandit based Monte-Carlo planning. In In: ECML-06. Number 4212 in LNCS, pages 282-293. Springer, 2006.
10. [Koval et al., 2014] Michael Koval, Nancy Pollard, and Siddhartha Srinivasa. Pre- and post-contact policy decomposition for planar contact manipulation under uncertainty. In RSS, Berkeley, USA, July 2014.
11. [Kurniawati and Patrikalakis, 2012] H. Kurniawati and N. M. Patrikalakis. Point-based policy transformation: adapting policy to changing POMDP models. In WAFR, 2012.
12. [Kurniawati and Yadav, 2013] H. Kurniawati and V. Yadav. An online POMDP solver for uncertainty planning in dynamic environment. In ISRR, 2013.
13. [Kurniawati et al., 2008] H. Kurniawati, D. Hsu, and W. S. Lee. SARSOP: Efficient point-based POMDP planning by approximating optimally reachable belief spaces. In RSS, 2008.
14. [Kurniawati et al., 2012] H. Kurniawati, T. Bandyopadhyay, and N. M. Patrikalakis. Global motion planning under uncertain motion, sensing, and environment map. Autonomous Robots: Special issue on RSS 2011, 30(3), 2012.
15. [Papadimitriou and Tsitsiklis, 1987] C. H. Papadimitriou and J. N. Tsitsiklis. The complexity of Markov decision processes. Math. of Operation Research, 12(3):441-450, 1987.
16. [Pineau et al., 2003] J. Pineau, G. Gordon, and S. Thrun. Pointbased value iteration: an anytime algorithm for POMDPs. In IJCAI, pages 1025-1032, 2003.
17. [Quigley et al., 2009] Morgan Quigley, Ken Conley, Brian Gerkey, Josh Faust, Tully B. Foote, Jeremy Leibs, Rob Wheeler, and Andrew Y. Ng. ROS: an open-source robot operating system. In ICRA Workshop on Open Source Software, 2009.
18. [Silver and Veness, 2010] D. Silver and J. Veness. Monte-Carlo planning in large POMDPs. In NIPS, 2010.
19. [Smith and Simmons, 2004] T. Smith and R. Simmons. Heuristic search value iteration for POMDPs. In UAI, 2004.
20. [Smith and Simmons, 2005] T. Smith and R. Simmons. Pointbased POMDP algorithms: improved analysis and implementation. In UAI, July 2005.
21. [Spaan and Vlassis, 2005] M. T. J. Spaan and N. Vlassis. Perseus: randomized point-based value iteration for POMDPs. JAIR, 24:195-220, 2005.
22. [Temizer et al., 2010] Selim Temizer, Mykel J Kochenderfer, Leslie P Kaelbling, Tomás Lozano-Pérez, and James K Kuchar. Collision avoidance for unmanned aircraft using Markov decision processes. In Proc. AIAA Guidance, Navigation, and Control Conference, 2010.
23. [Thrun, 2000] S. Thrun. Monte Carlo POMDPs. In NIPS, pages 1064-1070, 2000.