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

International Journal of Robotics Research

Volumn 30, Issue 7, 2011, Pages 895-913

  Van Den Berg, Jur ^a   Abbee, Pieter ^a,b   Goldberg, Ken ^b  

^a Brooks Computer Science Building   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Control; Planning; Uncertainty

Indexed keywords

CAR-LIKE ROBOT; DIJKSTRA'S ALGORITHMS; GAUSSIAN MODEL; HIGH QUALITY; KALMAN SMOOTHING; LINEAR QUADRATIC CONTROLLER; LINEAR QUADRATIC GAUSSIAN; MOTION UNCERTAINTY; MULTIROBOTS; PATH PLANNING FOR ROBOTS; RAPIDLY-EXPLORING RANDOM TREES; ROAD-MAPS; ROBOT MOTION PLANNING; SERIAL MANIPULATORS; SIMULATION EXPERIMENTS; STATE INFORMATION; UNCERTAINTY;

AUTOMOBILES; MANIPULATORS; MOTION PLANNING; PROBABILITY DISTRIBUTIONS; ROBOTS; UNCERTAINTY ANALYSIS;

ROBOT PROGRAMMING;

EID: 80052226681     PISSN: 02783649     EISSN: 17413176     Source Type: Journal    
DOI: 10.1177/0278364911406562     Document Type: Conference Paper

References (34)

1. Alterovitz R, Siméon T and Goldberg K (2007) The stochastic motion road-map: a sampling framework for planning with Markov motion uncertainty. In: Proceedings of Robotics: Science and Systems, 2007.
2. Bertsekas D (2001) Dynamic Programming and Optimal Control. Nashua, NH: Athena Scientific.
3. Bouilly B, Simeon T and Alami R (1995) A numerical technique for planning motion strategies of a mobile robot in presence of uncertainty. Proceedings of the IEEE International Conference on Robotics and Automation, 1995.
4. Burns B and Brock O (2007) Sampling-based motion planning with sensing uncertainty. In: Proceedings of the IEEE International Conference on Robotics and Automation, 2007.
5. Fraichard T and Mermond R (1998) Path planning with uncertainty for car-like robots. In: Proceedings of the IEEE International Conference on Robotics and Automation, 1998.
6. Geraerts R and Overmars M (2007) Creating high-quality paths for motion planning. The International Journal of Robotics Research 26: 845-863. (Pubitemid 47117239)
7. Gonzalez J and Stentz A (2009) Using linear landmarks for path planning with uncertainty in outdoor environments. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009.
8. Guibas L, Hsu D, Kurniawati H and Rehman E (2008) Bounded uncertainty roadmaps for path planning. In: Proceedings of the Workshop on Algorithmic Foundations of Robotics, 2008.
9. Huang Y and Gupta K (2009) Collision-probability constrained PRM for a manipulator with base pose uncertainty. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009.
10. Huynh V and Roy N (2009) icLQG: combining local and global optimization for control in information space. In: Proceedings of the IEEE International Conference on Robotics and Automation, 2009.
11. Kaelbling L, Littman M and Cassandra A (1998) Planning and acting in partially observable stochastic domains. Artificial Intelligence 101: 99-134. (Pubitemid 128387390)
12. Kavraki L, Svestka P, Latombe J-C and Overmars M (1996) Probabilistic roadmaps for path planning in high dimensional configuration spaces. IEEE Transactions on Robotics and Automation 12: 566-580. (Pubitemid 126774162)
13. Kewlani G, Ishigami G and Iagnemma K (2009) Stochastic mobility-based path planning in uncertain environments. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009.
14. Kuwata Y, Teo J, Karaman S, Fiore G, Frazzoli E and How J (2008) Motion planning in complex environments using closed-loop prediction. In: Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, 2008.
15. Kurniawati H, Hsu D and LeeW(2008) SARSOP: Efficient pointbased POMDP planning by approximating optimally reachable belief spaces. Proceedings of the Robotics: Science and Systems, 2008.
16. LaValle S (2006) Planning Algorithms. Cambridge: Cambridge University Press.
17. LaValle S and Hutchinson S (1998) An objective-based framework for motion planning under sensing and control uncertainties. The International Journal of Robotics Research 17: 19-42.
18. LaValle S and Kuffner J (2001) Randomized kinodynamic planning. The International Journal of Robotics Research 20: 378-400. (Pubitemid 32813681)
19. Lazanas A and Latombe J (1995) Motion planning with uncertainty: a landmark approach. Artificial Intelligence 76: 285-317.
20. Melchior N and Simmons R (2007) Particle RRT for path planning with uncertainty. In: Proceedings of the IEEE International Conference on Robotics and Automation, 2007.
21. Missiuro P and Roy N (2006) Adapting probabilistic roadmaps to handle uncertain maps. In: Proceedings of the IEEE International Conference on Robotics and Automation, 2006.
22. Nakhaei A and Lamiraux F (2008) A framework for planning motions in stochastic maps. In: Proceedings of the International Conference on Control, Automation, Robotics and Vision, 2008.
23. Papadimitriou C and Tsisiklis J (1987) The complexity of Markov decision processes. Mathematics of Operations Research 12: 441-450.
24. Pepy R and Lambert A (2006) Safe path planning in an uncertain- configuration space using RRT. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006.
25. Platt R, Tedrake R, Kaelbling L and Lozano-Perez T (2010) Belief space planning assuming maximum likelihood observations. In: Proceedings of the Robotics: Science and Systems, 2010.
26. Porta J, Vlassis N, Spaan M and Poupart P (2006) Point-based value iteration for continuous POMDPs. Journal of Machine Learning Research 7: 2329-2367. (Pubitemid 44708007)
27. Prentice S and Roy N (2009) The belief roadmap: efficient planning in belief space by factoring the covariance. The International Journal of Robotics Research 28: 1448-1465.
28. Rauch H, Tung F and Striebel C (1965) Maximum likelihood estimates of linear dynamic systems. AIAA Journal 3: 1445-1450.
29. Roy N, Burgard W, Fox D and Thrun S (1999) Coastal navigation-mobile robot navigation with uncertainty in dynamic environments. In: Proceedings of the IEEE International Conference on Robotics and Automation, 1999.
30. Tedrake R (2009) LQR-trees: Feedback motion planning on sparse randomized trees. In: Proceedings of the Robotics: Science and Systems, 2009.
31. Thrun S, Burgard W and Fox D (2005) Probabilistic Robotics. Cambridge, MA: The MIT Press.
32. van den Berg J and Overmars M (2005) Prioritized motion planning for multiple robots. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005.
33. van den Bergen G (2004) Collision Detection in Interactive 3D Environments. San Mateo, CA: Morgan Kaufmann.
34. Welch G and Bishop G (2006) An Introduction to the Kalman Filter.