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Volumn 6, Issue , 2011, Pages 129-136

LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information

Author keywords

[No Author keywords available]

Indexed keywords


EID: 84959558353     PISSN: None     EISSN: 2330765X     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (7)

References (32)
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  • 12
    • 0032073263 scopus 로고    scopus 로고
    • Planning and acting in partially observable stochastic domains
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    • (1998) Artificial Intelligence , vol.101 , Issue.1-2 , pp. 99-134
    • Kaelbling, L.1    Liftman, M.2    Cassandra, A.3
  • 16
    • 70349645087 scopus 로고    scopus 로고
    • SARSOP: Efficient point-based POMDP planning by approximating optimally reachable belief spaces
    • H. Kurniawati, D. Hsu, W. Lee. SARSOP: Efficient point-based POMDP planning by approximating optimally reachable belief spaces. Proc. Robotics: Science and Systems, 2008.
    • (2008) Proc. Robotics: Science and Systems
    • Kurniawati, H.1    Hsu, D.2    Lee, W.3
  • 17
    • 0031703630 scopus 로고    scopus 로고
    • An objective-based framework for motion planning under sensing and control uncertainties
    • S. LaValle, S. Hutchinson. An objective-based framework for motion planning under sensing and control uncertainties. Int. J. of Robotics Research 17(1): 19-42, 1998.
    • (1998) Int. J. of Robotics Research , vol.17 , Issue.1 , pp. 19-42
    • LaValle, S.1    Hutchinson, S.2
  • 20
    • 0029332309 scopus 로고
    • Motion planning with uncertainty: A landmark approach
    • A. Lazanas, J. Latombe. Motion planning with uncertainty: a landmark approach. Artificial Intelligence, 76(1-2): 285-317, 1995.
    • (1995) Artificial Intelligence , vol.76 , Issue.1-2 , pp. 285-317
    • Lazanas, A.1    Latombe, J.2
  • 27
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    • The belief roadmap: Efficient planning in linear POMDPs by factoring the covariance
    • S. Prentice, N. Roy. The belief roadmap: efficient planning in linear POMDPs by factoring the covariance. Proc. Int. Symp. of Robotics Research, 2008.
    • (2008) Proc. Int. Symp. of Robotics Research
    • Prentice, S.1    Roy, N.2
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    • LQR-trees: Feedback motion planning on sparse randomized trees
    • R. Tedrake. LQR-trees: Feedback motion planning on sparse randomized trees. Proc. Robotics: Science and Systems, 2009.
    • (2009) Proc. Robotics: Science and Systems
    • Tedrake, R.1
  • 31
    • 79955750805 scopus 로고    scopus 로고
    • An introduction to the Kalman filter
    • University of North Carolina at Chapel Hill
    • G. Welch, G. Bishop. An introduction to the Kalman filter. Tech. Report TR 95-041, University of North Carolina at Chapel Hill, 2006.
    • (2006) Tech. Report TR 95-041
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  • 32
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    • (2010) Chi-square Distribution


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.